Sorry for all of the packages. They grew and grew and grew, and I don’t want to refactor everything to reduce the dependencies.

library(raster)
library(data.table)
library(sf)
#RStoolbox has some dependencies like openMP that can be difficult to compile on a Mac (needed for the dependent package "caret"). If you have High Sierra OS or newer, search for instructions specific to your OS- it's a lot easier than older OS's.
library(RStoolbox)
library(leaflet)
library(plotly)
library(gdata)
library(BSDA)
library(ade4)
library(readxl)
library(janitor)
library(rnaturalearth)
library(adehabitatHS)
library(climateStability)
library(htmlwidgets)
library(tidyverse)
library(ggspatial)
library(here)
library(mapview)
library(fs)

r_path <- here::here("R")
source(file.path(r_path, "plot_leaflet_function.R")) #source locality plotting function
source(file.path(r_path, "plot_climate_pca_function.R")) #source pca plotting function
source(file.path(r_path, "species_pca_function.R")) #source function that computes climate pca per species
source(file.path(r_path, "min_convex_poly.R")) #source function that creates a minimum convex polygon around points
source(file.path(r_path, "enfa_calc_function.R"))
source(file.path(r_path, "marginality_lollipop_plot.R"))
source(file.path(r_path, "presence_absence_raster_function.R"))
source(file.path(r_path, "crop_background_env_function.R"))
source(file.path(r_path, "enfa_hex_plot.R"))
source(file.path(r_path, "total_climate_pca_plot.R"))
source(file.path(r_path, "raster_correlation_function.R"))
source(file.path(r_path, "move_to_species.R"))

Create subdirectories (if needed) and establish paths.

# function to check if subfolder exists. If not, make it
create_dir <- function(out_path) {
  if (!dir.exists(out_path)) {
    dir.create(out_path)
  } else
    print("Directory already there.")
}

# path for interactive plots, maps, etc. output
interactive_path <- here::here("output", "interactive_plots")

create_dir(precip_path)

# temperature climate data
temp_path <-
  here::here("data",
       "climate",
       "paleoclim_late_pleistocene",
       "temperature")

create_dir(temp_path)

# precipitation climate data
precip_path <-
  here::here("data",
       "climate",
       "paleoclim_late_pleistocene",
       "precipitation")

create_dir(precip_path)

# raster output
raster_path <- 
  here::here("output",
             "rasters")

create_dir(raster_path)

# map (non-interactive) output
map_path <- here::here("output", "maps")

create_dir(map_path)

# plot (non-interactive) output
plot_path <- here::here("output", "plots")

create_dir(plot_path)

# spreadsheet output
spread_path <- here::here("output", "spreadsheets")

create_dir(spread_path)

# R object (e.g. .RDS files) output
obj_path <- here::here("output", "objects")

create_dir(obj_path)

Read in the spreadsheet and take a look at the data.

# data path
loc_path <- here::here("data", "all species New_6-14-19.xlsx")

### read in spreadsheet
loc <- read_xlsx(loc_path) %>%
  janitor::clean_names() %>% 
  mutate(reproductive_mode = as.factor(reproductive_mode)) 

#get the number of individuals, and the sexuality counts per species
count_repro_mode <- loc %>% 
  group_by(genus, species, reproductive_mode) %>% 
  dplyr::count() %>% 
  mutate(genus_species = str_c(genus, species, sep = "_"),
         genus_species = str_replace_all(genus_species, " ", "_"),
         genus_species = str_replace_all(genus_species, "\\.", "")) %>% 
  ungroup() %>% 
  mutate(genus_species = fct_reorder(genus_species, n, sum)) %>% 
  ggplot(aes(x = genus_species, y = n, fill = reproductive_mode)) +
  geom_col() +
  coord_flip() + 
  theme_minimal()

count_repro_mode

Map

Plot a leaflet map of the localities. The leaflet map is interactive. You can click on the localities and a flag with some metadata will pop up!

PCA-Genera

PCA by locality

This is a PCA of the climate data extracted for each locality, rather than a PCA of the total climate space. This gives us a general idea of differences in environmental niche.

Run the pca and check out variable loadings and proportion of variance explained by components.

Two plots: One plot of the PCA colored according to genus, with convex hulls surrounding the genera. It looks like this reflects a latitudinal gradient in temperature! You can interact with the PCA plot by clicking on points to view associated metadata. You can isolate the genus you want to view by double clicking the genus in the legend! You can also remove a genus by clicking on it once. There’s some other functionality you can explore in the toolbar at the top of the plot. The second plot is a PCA colored according to reproductive mode. It looks like asexual populations occupy slightly larger niche space, but both reproductive modes have a similar niche center.

Examining whether asexual populations occupy more unstable climates than sexual populations. Only using species with multiple sexual and asexual populations. Asexual pops tend to occupy more stable temperature environments, but less stable precipitation environments. We’re estimating stability using the method presented by Owens and Guralnick 2019- climateStability: AN R PACKAGE TO ESTIMATE CLIMATE STABILITY FROM TIME-SLICE CLIMATOLOGIES.

### Creating temperature and precipitation stability layers
### Using bio1 (average temp) and bio12 (average precip)
### 2.5 arcmin resolution, already cropped to NZ to speed up computation time


#time slices are calculated as the difference between the midpoints of the two time periods the climate layers were calculated for (e.g. midpoint of LH = (4.2 ka - 0.3 ka) / 2 + 0.3 ka = 2.25, midpoint of MH = (8.326 ka - 4.2 ka) / 2 + 4.2 = 6.263. time_slice = 6.263 - 2.25 = 4.013)
time_slices <- c(2550, 4013, 6037, 1500, 2050, 5150)


precip_deviation <-
  climateStability::deviationThroughTime(variableDirectory = precip_path, timeSlicePeriod = time_slices)

precip_stability <- (1 / precip_deviation)
precip_stability_scaled <- climateStability::rescale0to1(precip_stability)

# write precipitation stability to file
writeRaster(
  precip_stability_scaled,
  filename = file.path(raster_path, "precip_stability_scaled.tif"),
  format = "GTiff"
)


temp_deviation <-
  climateStability::deviationThroughTime(variableDirectory = temp_path, timeSlicePeriod = time_slices)

temp_stability <- (1 / temp_deviation)
temp_stability_scaled <- climateStability::rescale0to1(temp_stability)

# write temperature stability to file
writeRaster(
  temp_stability_scaled,
  filename = file.path(raster_path, "temp_stability_scaled.tif"),
  format = "GTiff"
)

overall_stability_scaled <- precip_stability_scaled * temp_stability_scaled

# write overall stability to file
writeRaster(
  overall_stability_scaled,
  filename = file.path(raster_path, "overall_stability_scaled.tif"),
  format = "GTiff"
)

temp_stability_map <- ggplot() +
  ggspatial::layer_spatial(data = temp_stability_scaled) +
  labs(title = "Temperature stability") +
  scale_fill_viridis_c(na.value = "transparent") +
  theme_minimal()

precip_stability_map <- ggplot() +
  ggspatial::layer_spatial(data = precip_stability_scaled) +
  labs(title = "Precipitation stability") +
  scale_fill_viridis_c(na.value = "transparent") +
  theme_minimal()

overall_stability_map <- ggplot() +
  ggspatial::layer_spatial(data = overall_stability_scaled) +
  labs(title = "Overall stability") +
  scale_fill_viridis_c(na.value = "transparent") +
  theme_minimal()

temp_stability_map
precip_stability_map
overall_stability_map

ggsave("temp_stability.png",
       plot = temp_stability_map,
       device = "png",
       path = map_path,
       dpi = "retina")

ggsave("precip_stability.png",
       plot = precip_stability_map,
       device = "png",
       path = map_path,
       dpi = "retina")

ggsave("overall_stability.png",
       plot = overall_stability_map,
       device = "png",
       path = map_path,
       dpi = "retina")

Plot stability across species.


# filter for relevant species and asexual reproductive mode
asexual_locs <- loc %>%
  mutate(lat_long = str_c(latitude, longitude)) %>%
  filter(
    reproductive_mode == "asexual",
    species == "horridus" |
      species == "jucundum" |
      species == "hookeri" |
      species == "annulata" |
      species == "ovobessus" |
      species == "huttoni",
    !duplicated(lat_long)
  ) %>%
  dplyr::select(longitude, latitude)

# filter for relevant species and sexual reproductive mode
sexual_locs <- loc %>%
  mutate(lat_long = str_c(latitude, longitude)) %>%
  filter(
    reproductive_mode == "sexual",
    species == "horridus" |
      species == "jucundum" |
      species == "hookeri" |
      species == "annulata" |
      species == "ovobessus" |
      species == "huttoni",
    !duplicated(lat_long)
  ) %>%
  dplyr::select(longitude, latitude)

# extract preciptitation values and bind into a new dataframe
precip_asexual <-
  raster::extract(precip_stability_scaled, asexual_locs) %>%
  enframe(name = NULL, value = "precip_stability_scaled") %>%
  mutate(reproductive_mode = "asexual")

precip_sexual <-
  raster::extract(precip_stability_scaled, sexual_locs) %>%
  enframe(name = NULL, value = "precip_stability_scaled") %>%
  mutate(reproductive_mode = "sexual")

precip_df <- bind_rows(precip_asexual, precip_sexual)

# plot precipitation stability
precip_stability_plot <- ggplot(
  data = precip_df,
  aes(x = reproductive_mode, y = precip_stability_scaled, fill = reproductive_mode)
) +
  geom_violin(width = 0.8) +
  geom_boxplot(width = 0.1,
               color = "gray",
               fill = "transparent") +
  scale_fill_viridis_d(option = "magma") +
  theme_dark()

precip_stability_plot

# extract temperature values and bind into a new data frame
temp_asexual <-
  raster::extract(temp_stability_scaled, asexual_locs) %>%
  enframe(name = NULL, value = "temp_stability_scaled") %>%
  mutate(reproductive_mode = "asexual")

temp_sexual <-
  raster::extract(temp_stability_scaled, sexual_locs) %>%
  enframe(name = NULL, value = "temp_stability_scaled") %>%
  mutate(reproductive_mode = "sexual")

temp_df <- bind_rows(temp_asexual, temp_sexual)

# plot temperature stability
temp_stability_plot <- ggplot(data = temp_df,
       aes(x = reproductive_mode, y = temp_stability_scaled, fill = reproductive_mode)) +
  geom_violin(width = 0.8) +
  geom_boxplot(width = 0.1,
               color = "gray",
               fill = "transparent") +
  scale_fill_viridis_d(option = "magma") +
  theme_dark()

temp_stability_plot

# extract overall stability values and bind into a dataframe
overall_asexual <-
  raster::extract(overall_stability_scaled, asexual_locs) %>%
  enframe(name = NULL, value = "overall_stability_scaled") %>%
  mutate(reproductive_mode = "asexual")

overall_sexual <-
  raster::extract(overall_stability_scaled, sexual_locs) %>%
  enframe(name = NULL, value = "overall_stability_scaled") %>%
  mutate(reproductive_mode = "sexual")

overall_df <- bind_rows(overall_asexual, overall_sexual)

# plot overall stability
overall_stability_plot <- ggplot(
  data = overall_df,
  aes(x = reproductive_mode, y = overall_stability_scaled, fill = reproductive_mode)
) +
  geom_violin(width = 0.8) +
  geom_boxplot(width = 0.1,
               color = "gray",
               fill = "transparent") +
  scale_fill_viridis_d(option = "magma") +
  theme_dark()

overall_stability_plot

ggsave("temp_stability_plot.png",
       plot = temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

ggsave("precip_stability_plot.png",
       plot = precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

ggsave("overall_stability_plot.png",
       plot = overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

PCA-Species

These are PCAs of environmental space for species within genera. Each climate PCA is of localities for a single genus, colored by species. I’m doing this even for genera with one species, so it’s easy to see if certain localities group together.

Argosarchus

Now I’m going to to environmental niche factor analysis between sexual and asexual populations within the species.

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. The yellow dot indicates the mean marginality (it’s not the value that is on the lollipop plot, so don’t let that confuse you). 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations.

### 1) ENFA scatterplot
#access the relevant values for plotting
ahor_asexual_df <- ahor_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ahor_asexual_enfa$pr)

readr::write_csv(ahor_asexual_df, 
                 file.path(spread_path, "ahor_asexual_marginality_df.csv"))

ahor_sexual_df <- ahor_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ahor_sexual_enfa$pr)

readr::write_csv(ahor_sexual_df, 
                 file.path(spread_path, "ahor_sexual_marginality_df.csv"))

#asexual
ahor_enfa_spec_asexual <- enfa_hex_plot(ahor_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ahor_enfa_spec_asexual

ggsave("ahor_enfa_spec_asexual.png",
       plot = ahor_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
ahor_enfa_spec_sexual <- enfa_hex_plot(ahor_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ahor_enfa_spec_sexual

ggsave("ahor_enfa_spec_sexual.png",
       plot = ahor_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
## asexual
hist(ahor_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

# write to file
png(filename = file.path(plot_path, "ahor_asexual_enfa_hist.png"))
hist(ahor_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

## sexual
hist(ahor_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

# write to file
png(filename = file.path(plot_path, "ahor_sexual_enfa_hist.png"))
hist(ahor_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ahor_total_pca <- total_climate_pca_plot(bg_env = ahor_bg_env, locs = argo_loc, genus = "Argosarchus", species = "horridus")

ahor_total_pca

ggsave("ahor_total_pca.png",
       plot = ahor_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

Trying out a repeat of the analyses with reduced environmental space. Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we’re left with BIO6, BIO13, BIO14, BIO16

Repeat the analysis with the reduced data set. The background environment is 0.5 degrees, a ballpark dispersal limitation for all stick insect species in this study.

Visualize with reduced data set

### 1) ENFA scatterplot
#access the relevant values for plotting
ahor_asexual_df_subset <- ahor_asexual_enfa_subset$li %>%
  as_tibble() %>%
  bind_cols(pr = ahor_asexual_enfa_subset$pr)

readr::write_csv(
  ahor_asexual_df_subset,
  file.path(spread_path, "ahor_subset_asexual_marginality_df.csv")
)

ahor_sexual_df_subset <- ahor_sexual_enfa_subset$li %>%
  as_tibble() %>%
  bind_cols(pr = ahor_sexual_enfa_subset$pr)

readr::write_csv(
  ahor_sexual_df_subset,
  file.path(spread_path, "ahor_subset_sexual_marginality_df.csv")
)

#asexual. Jesus these variable names are getting long
ahor_subset_enfa_spec_asexual <-
  enfa_hex_plot(
    ahor_asexual_df_subset,
    marg = Mar,
    spec = Spe1,
    repro_mode = "Asexual"
  )

ahor_subset_enfa_spec_asexual

ggsave(
  "ahor_subset_enfa_spec_asexual.png",
  plot = ahor_subset_enfa_spec_asexual,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

# sexual
ahor_subset_enfa_spec_sexual <-
  enfa_hex_plot(
    ahor_sexual_df_subset,
    marg = Mar,
    spec = Spe1,
    repro_mode = "Sexual"
  )

ahor_subset_enfa_spec_sexual

ggsave(
  "ahor_subset_enfa_spec_sexual.png",
  plot = ahor_subset_enfa_spec_sexual,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

### 2) ENFA histogram
# asexual
hist(ahor_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ahor_subset_asexual_enfa_hist.png"))
hist(ahor_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

# sexual
hist(ahor_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ahor_subset_sexual_enfa_hist.png"))
hist(ahor_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ahor_subset_total_pca <-
  total_climate_pca_plot(
    bg_env = ahor_bg_env_subset,
    locs = argo_loc,
    genus = "Argosarchus",
    species = "horridus"
  )

ahor_subset_total_pca

ggsave(
  "ahor_subset_total_pca.png",
  plot = ahor_subset_total_pca,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(ahor_sexual_enfa, file = file.path(obj_path, "ahor_sexual_enfa.RDS"))
rm(ahor_sexual_enfa)

saveRDS(ahor_asexual_enfa, file = file.path(obj_path, "ahor_asexual_enfa.RDS"))
rm(ahor_asexual_enfa)

saveRDS(ahor_sexual_enfa_subset,
        file = file.path(obj_path, "ahor_subset_sexual_enfa.RDS"))
rm(ahor_sexual_enfa_subset)

saveRDS(ahor_asexual_enfa_subset,
        file = file.path(obj_path, "ahor_subset_asexual_enfa.RDS"))
rm(ahor_asexual_enfa_subset)

We’re also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations.

argo_locs_asexual <- argo_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

argo_locs_sexual <- argo_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_ahor <- raster::extract(precip_stability_scaled, argo_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_ahor <- raster::extract(precip_stability_scaled, argo_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_ahor <- bind_rows(precip_asexual_ahor, precip_sexual_ahor)

readr::write_csv(precip_df_ahor, 
                 file.path(spread_path, "ahor_precip_stability_df.csv"))

ahor_precip_stability_plot <- ggplot(data = precip_df_ahor, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ahor_precip_stability_plot

ggsave(
  "ahor_precip_stability.png",
  plot = ahor_precip_stability_plot,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

temp_asexual_ahor <- raster::extract(temp_stability_scaled, argo_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_ahor <- raster::extract(temp_stability_scaled, argo_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_ahor <- bind_rows(temp_asexual_ahor, temp_sexual_ahor)

readr::write_csv(temp_df_ahor, 
                 file.path(spread_path, "ahor_temp_stability_df.csv"))

ahor_temp_stability_plot <- ggplot(data = temp_df_ahor, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ahor_temp_stability_plot

ggsave(
  "ahor_temp_stability.png",
  plot = ahor_temp_stability_plot,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

overall_asexual_ahor <- raster::extract(overall_stability_scaled, argo_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_ahor <- raster::extract(overall_stability_scaled, argo_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_ahor <- bind_rows(overall_asexual_ahor, overall_sexual_ahor)

readr::write_csv(overall_df_ahor, 
                 file.path(spread_path, "ahor_overall_stability_df.csv"))


ahor_overall_stability_plot <- ggplot(data = overall_df_ahor, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ahor_overall_stability_plot

ggsave(
  "ahor_overall_stability.png",
  plot = ahor_overall_stability_plot,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

Put all output into species-specific subfolders.

Asteliaphasma

Now I’m going to to environmental niche factor analysis between sexual and asexual populations within the species.

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations.

### 1) ENFA scatterplot
#access the relevant values for plotting
ajuc_asexual_df <- ajuc_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_asexual_enfa$pr)

readr::write_csv(ajuc_asexual_df, 
                 file.path(spread_path, "ajuc_asexual_marginality_df.csv"))


ajuc_sexual_df <- ajuc_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_sexual_enfa$pr)

readr::write_csv(ajuc_sexual_df, 
                 file.path(spread_path, "ajuc_sexual_marginality_df.csv"))

#asexual
ajuc_enfa_spec_asexual <- enfa_hex_plot(ajuc_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("ajuc_enfa_spec_asexual.png",
       plot = ajuc_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
ajuc_enfa_spec_sexual <- enfa_hex_plot(ajuc_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("ajuc_enfa_spec_sexual.png",
       plot = ajuc_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(ajuc_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_asexual_enfa_hist.png"))
hist(ajuc_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

# sexual
hist(ajuc_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_sexual_enfa_hist.png"))
hist(ajuc_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ajuc_total_pca <- total_climate_pca_plot(bg_env = ajuc_bg_env, locs = aste_loc, genus = "Asteliophasma", species = "jucundum")

ajuc_total_pca

ggsave("ajuc_total_pca.png",
       plot = ajuc_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

Trying out a repeat of the analyses with reduced environmental space. Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we’re left with BIO5, BIO6, BIO14, BIO17.

Repeat the analysis with the reduced data set.

Visualize with the reduced data set.

### 1) ENFA scatterplot
# access the relevant values for plotting
ajuc_asexual_df_subset <- ajuc_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_asexual_enfa_subset$pr)

readr::write_csv(
  ajuc_asexual_df_subset,
  file.path(spread_path, "ajuc_asexual_df_subset.csv")
)


ajuc_sexual_df_subset <- ajuc_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_sexual_enfa_subset$pr)

readr::write_csv(
  ajuc_sexual_df_subset,
  file.path(spread_path, "ajuc_sexual_df_subset.csv")
)

# asexual
ajuc_subset_enfa_spec_asexual <- enfa_hex_plot(ajuc_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("ajuc_subset_enfa_spec_asexual.png",
       plot = ajuc_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
ajuc_subset_enfa_spec_sexual <- enfa_hex_plot(ajuc_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("ajuc_subset_enfa_spec_sexual.png",
       plot = ajuc_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(ajuc_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_subset_asexual_enfa_hist.png"))
hist(ajuc_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(ajuc_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_subset_sexual_enfa_hist.png"))
hist(ajuc_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ajuc_subset_total_pca <- total_climate_pca_plot(bg_env = ajuc_bg_env_subset, locs = aste_loc, genus = "Asteliaphasma", species = "jucundum")

ggsave("ajuc_subset_total_pca.png",
       plot = ajuc_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(ajuc_sexual_enfa, file = file.path(obj_path, "ajuc_sexual_enfa.RDS"))
rm(ajuc_sexual_enfa)

saveRDS(ajuc_asexual_enfa, file = file.path(obj_path, "ajuc_asexual_enfa.RDS"))
rm(ajuc_asexual_enfa)

saveRDS(ajuc_sexual_enfa_subset,
        file = file.path(obj_path, "ajuc_subset_sexual_enfa.RDS"))
rm(ajuc_sexual_enfa_subset)

saveRDS(ajuc_asexual_enfa_subset,
        file = file.path(obj_path, "ajuc_subset_asexual_enfa.RDS"))
rm(ajuc_asexual_enfa_subset)

We’re also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations.

aste_locs_asexual <- aste_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

aste_locs_sexual <- aste_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_ajuc <- raster::extract(precip_stability_scaled, aste_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_ajuc <- raster::extract(precip_stability_scaled, aste_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_ajuc <- bind_rows(precip_asexual_ajuc, precip_sexual_ajuc)

readr::write_csv(precip_df_ajuc, 
                 file.path(spread_path, "ajuc_precip_stability_df.csv"))

ajuc_precip_stability_plot <- ggplot(data = precip_df_ajuc, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ggsave("ajuc_precip_stability.png",
       plot = ajuc_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_ajuc <- raster::extract(temp_stability_scaled, aste_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_ajuc <- raster::extract(temp_stability_scaled, aste_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_ajuc <- bind_rows(temp_asexual_ajuc, temp_sexual_ajuc)

readr::write_csv(temp_df_ajuc, 
                 file.path(spread_path, "ajuc_temp_stability_df.csv"))

ajuc_temp_stability_plot <- ggplot(data = temp_df_ajuc, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ggsave("ajuc_precip_stability.png",
       plot = ajuc_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_ajuc <- raster::extract(overall_stability_scaled, aste_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_ajuc <- raster::extract(overall_stability_scaled, aste_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_ajuc <- bind_rows(overall_asexual_ajuc, overall_sexual_ajuc)

readr::write_csv(overall_df_ajuc, 
                 file.path(spread_path, "ajuc_overall_stability_df.csv"))

ajuc_overall_stability_plot <- ggplot(data = overall_df_ajuc, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ggsave("ajuc_overall_stability.png",
       plot = ajuc_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

Put all output into species-specific subfolders.

Clitarchus

Now I’m going to perform environmental niche factor analysis with sexual and asexual populations within the species.

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations.

### 1) ENFA scatterplot
#access the relevant values for plotting
choo_asexual_df <- choo_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_asexual_enfa$pr)

readr::write_csv(choo_asexual_df, 
                 file.path(spread_path, "choo_asexual_marginality_df.csv"))

choo_sexual_df <- choo_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_sexual_enfa$pr)

readr::write_csv(choo_sexual_df, 
                 file.path(spread_path, "choo_sexual_marginality_df.csv"))

# asexual
choo_enfa_spec_asexual <- enfa_hex_plot(choo_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("choo_enfa_spec_asexual.png",
       plot = choo_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
choo_enfa_spec_sexual <- enfa_hex_plot(choo_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("choo_enfa_spec_sexual.png",
       plot = choo_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(choo_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_asexual_enfa_hist.png"))
hist(choo_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

#sexual
hist(choo_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_sexual_enfa_hist.png"))
hist(choo_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
choo_total_pca <- total_climate_pca_plot(bg_env = choo_bg_env, locs = clita_loc, genus = "Clitarchus", species = "hookeri")

choo_total_pca

ggsave("choo_total_pca.png",
       plot = choo_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

Trying out a repeat of the analyses with reduced environmental space. Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we’re left with BIO8, BIO11, BIO15, BIO17.

Repeat the analysis with the reduced data set.

Visualize with the reduced data set.

### 1) ENFA scatterplot
# access the relevant values for plotting
choo_asexual_df_subset <- choo_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_asexual_enfa_subset$pr)

readr::write_csv(
  choo_asexual_df_subset,
  file.path(spread_path, "choo_asexual_df_subset.csv")
)


choo_sexual_df_subset <- choo_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_sexual_enfa_subset$pr)

readr::write_csv(
  choo_sexual_df_subset,
  file.path(spread_path, "choo_sexual_df_subset.csv")
)

# asexual
choo_subset_enfa_spec_asexual <- enfa_hex_plot(choo_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("choo_subset_enfa_spec_asexual.png",
       plot = choo_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
choo_subset_enfa_spec_sexual <- enfa_hex_plot(choo_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("choo_subset_enfa_spec_sexual.png",
       plot = choo_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(choo_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_subset_asexual_enfa_hist.png"))
hist(choo_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(choo_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_subset_sexual_enfa_hist.png"))
hist(choo_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
choo_subset_total_pca <- total_climate_pca_plot(bg_env = choo_bg_env_subset, locs = clita_loc, genus = "Clitarchus", species = "hookeri")

choo_subset_total_pca

ggsave("choo_subset_total_pca.png",
       plot = choo_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(choo_sexual_enfa, file = file.path(obj_path, "choo_sexual_enfa.RDS"))
rm(choo_sexual_enfa)

saveRDS(choo_asexual_enfa, file = file.path(obj_path, "choo_asexual_enfa.RDS"))
rm(choo_asexual_enfa)

saveRDS(choo_sexual_enfa_subset,
        file = file.path(obj_path, "choo_subset_sexual_enfa.RDS"))
rm(choo_sexual_enfa_subset)

saveRDS(choo_asexual_enfa_subset,
        file = file.path(obj_path, "choo_subset_asexual_enfa.RDS"))
rm(choo_asexual_enfa_subset)

We’re also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations.

clita_locs_asexual <- clita_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

clita_locs_sexual <- clita_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_choo <- raster::extract(precip_stability_scaled, clita_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_choo <- raster::extract(precip_stability_scaled, clita_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_choo <- bind_rows(precip_asexual_choo, precip_sexual_choo)

readr::write_csv(precip_df_choo, 
                 file.path(spread_path, "choo_precip_stability_df.csv"))

choo_precip_stability_plot <- ggplot(data = precip_df_choo, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

choo_precip_stability_plot

ggsave("choo_precip_stability.png",
       plot = choo_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_choo <- raster::extract(temp_stability_scaled, clita_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_choo <- raster::extract(temp_stability_scaled, clita_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_choo <- bind_rows(temp_asexual_choo, temp_sexual_choo)

readr::write_csv(temp_df_choo, 
                 file.path(spread_path, "choo_temp_stability_df.csv"))

choo_temp_stability_plot <- ggplot(data = temp_df_choo, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

choo_temp_stability_plot

ggsave("choo_precip_stability.png",
       plot = choo_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_choo <- raster::extract(overall_stability_scaled, clita_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_choo <- raster::extract(overall_stability_scaled, clita_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_choo <- bind_rows(overall_asexual_choo, overall_sexual_choo)

readr::write_csv(overall_df_choo, 
                 file.path(spread_path, "choo_overall_stability_df.csv"))

choo_overall_stability_plot <- ggplot(data = overall_df_choo, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

choo_overall_stability_plot

ggsave("choo_overall_stability.png",
       plot = choo_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

Put all output into species-specific subfolders.

Niveaphasma

Now I’m going to perform environmental niche factor analysis with sexual and asexual populations within the species.

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations.

### 1) ENFA scatterplot
#access the relevant values for plotting
nive_asexual_df <- nive_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_asexual_enfa$pr)

readr::write_csv(nive_asexual_df, 
                 file.path(spread_path, "nive_asexual_marginality_df.csv"))

nive_sexual_df <- nive_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_sexual_enfa$pr)

readr::write_csv(nive_sexual_df, 
                 file.path(spread_path, "nive_sexual_marginality_df.csv"))

# asexual
nive_enfa_spec_asexual <- enfa_hex_plot(nive_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("nive_enfa_spec_asexual.png",
       plot = nive_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
nive_enfa_spec_sexual <- enfa_hex_plot(nive_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("nive_enfa_spec_sexual.png",
       plot = nive_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(nive_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_asexual_enfa_hist.png"))
hist(nive_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

#sexual
hist(nive_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_sexual_enfa_hist.png"))
hist(nive_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
nive_total_pca <- total_climate_pca_plot(bg_env = nive_bg_env, locs = nive_loc, genus = "Niveaphasma", species = "annulata")

nive_total_pca

ggsave("nive_total_pca.png",
       plot = nive_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

Trying out a repeat of the analyses with reduced environmental space. Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we’re left with BIO4, BIO8, BIO9, BIO11, BIO15, BIO17

Repeat the analysis with the reduced data set.

Visualize with the reduced data set.

### 1) ENFA scatterplot
# access the relevant values for plotting
nive_asexual_df_subset <- nive_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_asexual_enfa_subset$pr)

readr::write_csv(
  nive_asexual_df_subset,
  file.path(spread_path, "nive_asexual_df_subset.csv")
)


nive_sexual_df_subset <- nive_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_sexual_enfa_subset$pr)

readr::write_csv(
  nive_sexual_df_subset,
  file.path(spread_path, "nive_sexual_df_subset.csv")
)

# asexual
nive_subset_enfa_spec_asexual <- enfa_hex_plot(nive_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("nive_subset_enfa_spec_asexual.png",
       plot = nive_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
nive_subset_enfa_spec_sexual <- enfa_hex_plot(nive_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("nive_subset_enfa_spec_sexual.png",
       plot = nive_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(nive_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_subset_asexual_enfa_hist.png"))
hist(nive_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(nive_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_subset_sexual_enfa_hist.png"))
hist(nive_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
nive_subset_total_pca <- total_climate_pca_plot(bg_env = nive_bg_env_subset, locs = nive_loc, genus = "Niveaphasma", species = "annulata")

nive_subset_total_pca

ggsave("nive_subset_total_pca.png",
       plot = nive_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(nive_sexual_enfa, file = file.path(obj_path, "nive_sexual_enfa.RDS"))
rm(nive_sexual_enfa)

saveRDS(nive_asexual_enfa, file = file.path(obj_path, "nive_asexual_enfa.RDS"))
rm(nive_asexual_enfa)

saveRDS(nive_sexual_enfa_subset,
        file = file.path(obj_path, "nive_subset_sexual_enfa.RDS"))
rm(nive_sexual_enfa_subset)

saveRDS(nive_asexual_enfa_subset,
        file = file.path(obj_path, "nive_subset_asexual_enfa.RDS"))
rm(nive_asexual_enfa_subset)

We’re also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations.

Put all output into species-specific subfolders.

Spinotectarchus

Assuming "longitude" and "latitude" are longitude and latitude, respectively

Importance of components:
                          PC1    PC2     PC3     PC4
Standard deviation     3.2695 2.2059 1.34553 0.86655
Proportion of Variance 0.5626 0.2561 0.09529 0.03952
Cumulative Proportion  0.5626 0.8187 0.91400 0.95352
                           PC5     PC6     PC7     PC8
Standard deviation     0.74273 0.46863 0.17686 0.16724
Proportion of Variance 0.02903 0.01156 0.00165 0.00147
Cumulative Proportion  0.98255 0.99411 0.99576 0.99723
                           PC9    PC10    PC11    PC12
Standard deviation     0.13032 0.11326 0.10151 0.07549
Proportion of Variance 0.00089 0.00068 0.00054 0.00030
Cumulative Proportion  0.99813 0.99880 0.99934 0.99964
                          PC13    PC14    PC15    PC16
Standard deviation     0.05244 0.04105 0.03104 0.02296
Proportion of Variance 0.00014 0.00009 0.00005 0.00003
Cumulative Proportion  0.99979 0.99988 0.99993 0.99995
                          PC17    PC18    PC19
Standard deviation     0.02110 0.01685 0.01122
Proportion of Variance 0.00002 0.00001 0.00001
Cumulative Proportion  0.99998 0.99999 1.00000
PC1 PC2 PC3
bio1 -0.279 -0.111 -0.222
bio10 -0.273 -0.057 -0.287
bio11 -0.277 -0.149 -0.177
bio12 0.243 -0.262 -0.125
bio13 0.200 -0.325 -0.111
bio14 0.246 -0.230 -0.069
bio15 -0.133 -0.273 -0.034
bio16 0.209 -0.314 -0.127
bio17 0.254 -0.217 -0.105
bio18 0.231 -0.236 -0.143
bio19 0.216 -0.303 -0.134
bio2 0.199 0.274 -0.319
bio3 0.174 0.238 -0.438
bio4 0.225 0.267 -0.029
bio5 -0.165 0.138 -0.577
bio6 -0.274 -0.193 -0.055
bio7 0.217 0.281 -0.234
bio8 -0.272 -0.165 -0.177
bio9 -0.206 -0.046 -0.144

Tectarchus

Assuming "longitude" and "latitude" are longitude and latitude, respectively

Importance of components:
                          PC1    PC2    PC3     PC4
Standard deviation     2.8207 2.5946 1.6199 0.97671
Proportion of Variance 0.4188 0.3543 0.1381 0.05021
Cumulative Proportion  0.4188 0.7731 0.9112 0.96139
                          PC5     PC6     PC7     PC8
Standard deviation     0.5929 0.41322 0.34989 0.24011
Proportion of Variance 0.0185 0.00899 0.00644 0.00303
Cumulative Proportion  0.9799 0.98888 0.99532 0.99836
                          PC9    PC10    PC11    PC12
Standard deviation     0.1152 0.08270 0.06439 0.04904
Proportion of Variance 0.0007 0.00036 0.00022 0.00013
Cumulative Proportion  0.9991 0.99942 0.99964 0.99976
                          PC13    PC14    PC15    PC16
Standard deviation     0.03772 0.03410 0.02871 0.02481
Proportion of Variance 0.00007 0.00006 0.00004 0.00003
Cumulative Proportion  0.99984 0.99990 0.99994 0.99997
                          PC17    PC18    PC19
Standard deviation     0.01599 0.01130 0.01040
Proportion of Variance 0.00001 0.00001 0.00001
Cumulative Proportion  0.99999 0.99999 1.00000
PC1 PC2 PC3
bio1 0.333 0.031 -0.196
bio10 0.310 0.021 -0.288
bio11 0.345 0.031 -0.113
bio12 0.050 -0.380 0.020
bio13 0.071 -0.367 0.088
bio14 0.032 -0.379 -0.011
bio15 0.101 0.106 0.274
bio16 0.072 -0.368 0.077
bio17 0.029 -0.379 -0.010
bio18 0.020 -0.378 -0.015
bio19 0.083 -0.352 0.080
bio2 -0.279 -0.061 -0.354
bio3 -0.251 -0.056 -0.361
bio4 -0.300 -0.047 -0.286
bio5 0.215 -0.009 -0.481
bio6 0.351 0.044 -0.020
bio7 -0.284 -0.063 -0.344
bio8 0.274 0.009 -0.209
bio9 0.293 0.048 -0.198

Tectarchus ovobessus

Now I’m going to perform environmental niche factor analysis with sexual and asexual populations within the species.

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations.

quartz_off_screen 
                2 

quartz_off_screen 
                2

Trying out a repeat of the analyses with reduced environmental space. Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we’re left with BIO4, BIO8, BIO11, BIO15, BIO17

Var1 Var2 value
bio1 bio9 0.7683085
bio1 bio5 0.9431235
bio10 bio9 0.7649972
bio10 bio5 0.9696441
bio10 bio1 0.9949074
bio11 bio9 0.7840988
bio11 bio5 0.9097998
bio11 bio1 0.9941228
bio11 bio10 0.9798860
bio6 bio9 0.7634527
bio6 bio5 0.8549377
bio6 bio1 0.9774484
bio6 bio10 0.9527160
bio6 bio11 0.9924265
bio12 bio19 0.9303682
bio13 bio19 0.9494262
bio13 bio12 0.9904545
bio16 bio19 0.9503474
bio16 bio12 0.9911887
bio16 bio13 0.9993100
bio18 bio19 0.8488702
bio18 bio12 0.9765329
bio18 bio13 0.9544060
bio18 bio16 0.9557642
bio14 bio19 0.8939441
bio14 bio12 0.9862519
bio14 bio13 0.9664429
bio14 bio16 0.9680861
bio14 bio18 0.9878180
bio17 bio19 0.8861880
bio17 bio12 0.9881415
bio17 bio13 0.9676936
bio17 bio16 0.9693849
bio17 bio18 0.9875497
bio17 bio14 0.9958281
bio4 bio6 -0.8042062
bio2 bio3 0.9469371
bio2 bio4 0.8977292
bio7 bio3 0.8829596
bio7 bio4 0.9549837
bio7 bio2 0.9835939

Repeat the analysis with the reduced data set.

Visualize with the reduced data set.

quartz_off_screen 
                2 

quartz_off_screen 
                2

We’re also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations.

Put all output into species-specific subfolders.

Tectarchus huttoni

Now I’m going to perform environmental niche factor analysis with sexual and asexual populations within the species.

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations.

quartz_off_screen 
                2 

quartz_off_screen 
                2

Trying out a repeat of the analyses with reduced environmental space. Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we’re left with BIO4, BIO8, BIO11, BIO15, BIO17

Var1 Var2 value
bio1 bio9 0.7683085
bio1 bio5 0.9431235
bio10 bio9 0.7649972
bio10 bio5 0.9696441
bio10 bio1 0.9949074
bio11 bio9 0.7840988
bio11 bio5 0.9097998
bio11 bio1 0.9941228
bio11 bio10 0.9798860
bio6 bio9 0.7634527
bio6 bio5 0.8549377
bio6 bio1 0.9774484
bio6 bio10 0.9527160
bio6 bio11 0.9924265
bio12 bio19 0.9303682
bio13 bio19 0.9494262
bio13 bio12 0.9904545
bio16 bio19 0.9503474
bio16 bio12 0.9911887
bio16 bio13 0.9993100
bio18 bio19 0.8488702
bio18 bio12 0.9765329
bio18 bio13 0.9544060
bio18 bio16 0.9557642
bio14 bio19 0.8939441
bio14 bio12 0.9862519
bio14 bio13 0.9664429
bio14 bio16 0.9680861
bio14 bio18 0.9878180
bio17 bio19 0.8861880
bio17 bio12 0.9881415
bio17 bio13 0.9676936
bio17 bio16 0.9693849
bio17 bio18 0.9875497
bio17 bio14 0.9958281
bio4 bio6 -0.8042062
bio2 bio3 0.9469371
bio2 bio4 0.8977292
bio7 bio3 0.8829596
bio7 bio4 0.9549837
bio7 bio2 0.9835939

Repeat the analysis with the reduced data set.

Visualize with the reduced data set.

quartz_off_screen 
                2 

quartz_off_screen 
                2

We’re also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations.

Put all output into species-specific subfolders.

Tepakiphasma

Nothing. Only one locality.

Convenience scripts

These scripts aren’t crucial for reproducing this analysis, but were helpful for various reasons. Some of these have hard-coded paths and such, so no guarantees for use right out of the box.

This was a script I used to take full chelsa files, crop them to New Zealand extent, and write them to a file with my personal computer. I don’t have much memory, so unzipping to a temporary directory, then deleting the directory to free up space for the large files worked.

---
title: "Stick Insect Climate PCA"
output: 
  html_notebook:
    theme: flatly
    highlight: tango
---

Sorry for all of the packages. They grew and grew and grew, and I don't want to refactor everything to reduce the dependencies.

```{r message=FALSE}
library(raster)
library(data.table)
library(sf)
#RStoolbox has some dependencies like openMP that can be difficult to compile on a Mac (needed for the dependent package "caret"). If you have High Sierra OS or newer, search for instructions specific to your OS- it's a lot easier than older OS's.
library(RStoolbox)
library(leaflet)
library(plotly)
library(gdata)
library(BSDA)
library(ade4)
library(readxl)
library(janitor)
library(rnaturalearth)
library(adehabitatHS)
library(climateStability)
library(htmlwidgets)
library(tidyverse)
library(ggspatial)
library(here)
library(mapview)
library(fs)

r_path <- here::here("R")
source(file.path(r_path, "plot_leaflet_function.R")) #source locality plotting function
source(file.path(r_path, "plot_climate_pca_function.R")) #source pca plotting function
source(file.path(r_path, "species_pca_function.R")) #source function that computes climate pca per species
source(file.path(r_path, "min_convex_poly.R")) #source function that creates a minimum convex polygon around points
source(file.path(r_path, "enfa_calc_function.R"))
source(file.path(r_path, "marginality_lollipop_plot.R"))
source(file.path(r_path, "presence_absence_raster_function.R"))
source(file.path(r_path, "crop_background_env_function.R"))
source(file.path(r_path, "enfa_hex_plot.R"))
source(file.path(r_path, "total_climate_pca_plot.R"))
source(file.path(r_path, "raster_correlation_function.R"))
source(file.path(r_path, "move_to_species.R"))
```

Create subdirectories (if needed) and establish paths.
```{r}
# function to check if subfolder exists. If not, make it
create_dir <- function(out_path) {
  if (!dir.exists(out_path)) {
    dir.create(out_path)
  } else
    print("Directory already there.")
}

# path for interactive plots, maps, etc. output
interactive_path <- here::here("output", "interactive_plots")

create_dir(precip_path)

# temperature climate data
temp_path <-
  here::here("data",
       "climate",
       "paleoclim_late_pleistocene",
       "temperature")

create_dir(temp_path)

# precipitation climate data
precip_path <-
  here::here("data",
       "climate",
       "paleoclim_late_pleistocene",
       "precipitation")

create_dir(precip_path)

# raster output
raster_path <- 
  here::here("output",
             "rasters")

create_dir(raster_path)

# map (non-interactive) output
map_path <- here::here("output", "maps")

create_dir(map_path)

# plot (non-interactive) output
plot_path <- here::here("output", "plots")

create_dir(plot_path)

# spreadsheet output
spread_path <- here::here("output", "spreadsheets")

create_dir(spread_path)

# R object (e.g. .RDS files) output
obj_path <- here::here("output", "objects")

create_dir(obj_path)

```



Read in the spreadsheet and take a look at the data.

```{r}
# data path
loc_path <- here::here("data", "all species New_6-14-19.xlsx")

### read in spreadsheet
loc <- read_xlsx(loc_path) %>%
  janitor::clean_names() %>% 
  mutate(reproductive_mode = as.factor(reproductive_mode)) 

#get the number of individuals, and the sexuality counts per species
count_repro_mode <- loc %>% 
  group_by(genus, species, reproductive_mode) %>% 
  dplyr::count() %>% 
  mutate(genus_species = str_c(genus, species, sep = "_"),
         genus_species = str_replace_all(genus_species, " ", "_"),
         genus_species = str_replace_all(genus_species, "\\.", "")) %>% 
  ungroup() %>% 
  mutate(genus_species = fct_reorder(genus_species, n, sum)) %>% 
  ggplot(aes(x = genus_species, y = n, fill = reproductive_mode)) +
  geom_col() +
  coord_flip() + 
  theme_minimal()

count_repro_mode
```

## Map
Plot a leaflet map of the localities. The leaflet map is interactive. You can click on the localities and a flag with some metadata will pop up! 

```{r warning=FALSE, message=FALSE}
#make locality shape file and assign WGS coord system
coord_points <- st_as_sf(loc, coords = c("longitude", "latitude"), 
                         crs = 4326, agr = "constant")

#use sourced plot_locs_leaflet script to plot localities
all_plot <- plot_locs_leaflet(loc, "reproductive_mode")

all_plot

# save the map
mapview::mapshot(
  all_plot,
  url = file.path(interactive_path, "all_species_map.html"),
  file = file.path(interactive_path, "all_species_map.pdf")
)
```

## PCA-Genera {.tabset}

### Climate Data
Read in the bioclim layers for analysis. I'm using all 19 for this preliminary exploration. I'm using CHELSA v1.2 data downloaded from [their website](http://chelsa-climate.org/downloads/). Plotting the first temperature layer to take a look at the data.
```{r cache=TRUE}
clim_files <- here::here("data", "climate") %>% 
  list.files(pattern = ".tif", full.names = TRUE)

w <- stack(clim_files)

#shorten the names of the bioclims
names(w) <- paste0(
  stringr::str_extract(names(w), "bio"), 
  stringr::str_extract(names(w), "\\d+$")
  )


ggplot() +
  ggspatial::layer_spatial(data = w[[1]]) +
  scale_fill_viridis_c(na.value = "transparent") +
  labs(fill = "Annual Avg Temp (C*10)") +
  theme_minimal()
  
```


### PCA by locality
This is a PCA of the climate data extracted for each locality, rather than a PCA of the total climate space. This gives us a general idea of differences in environmental niche.

Run the pca and check out variable loadings and proportion of variance explained by components.

```{r cache=TRUE}
#extract data from chelsa for each locality. Making this into a data frame with columns labeled so the row labeling lines up after I remove the NAs.
#extract data from worldclim for each locality.
coords <- data.frame(latitude = loc$longitude, longitude = loc$latitude)

loc_clim <- dplyr::bind_cols(loc, raster::extract(w, coords, method = "simple", df = TRUE)) %>% 
  drop_na(bio1) %>% 
  dplyr::select(-ID)

#make a matrix of only bioclim values
clim_mat <- loc_clim[,grep("bio", names(loc_clim))] %>% as.matrix()

#run pca on climate variables
clim_pca <- prcomp(clim_mat, scale = TRUE)
summary_pca <- summary(clim_pca) #check out the components

#plot tables
summary_pca
knitr::kable(round(clim_pca$rotation[,1:3],3)) #Table of loading scores for the first 3 PCs.

```

Two plots: One plot of the PCA colored according to genus, with convex hulls surrounding the genera. It looks like this reflects a latitudinal gradient in temperature! You can interact with the PCA plot by clicking on points to view associated metadata. You can isolate the genus you want to view by double clicking the genus in the legend! You can also remove a genus by clicking on it once. There's some other functionality you can explore in the toolbar at the top of the plot. The second plot is a PCA colored according to reproductive mode. It looks like asexual populations occupy slightly larger niche space, but both reproductive modes have a similar niche center.
```{r warning=FALSE}
#add pca results to loc_clim data frame
loc_clim <- data.frame(loc_clim, clim_pca$x)

#use sourced plot_clim_pca function to plot the pca results. args are the data set with species names and PC axis values and the pca summary
all_pca <- plot_clim_pca(loc_clim, summary_pca, factor = "genus")
all_pca

#use sourced plot_clim_pca function to plot the pca results. args are the data set with species names and PC axis values and the pca summary
repro_pca <-
  plot_clim_pca(loc_clim, summary_pca, factor = "reproductive_mode")
repro_pca


# save the plot colored by genus
htmlwidgets::saveWidget(
  all_pca,
  file.path(interactive_path, "all_species_pca_genus.html"),
  selfcontained = TRUE
)

# save the plot colored by reproductive mode
htmlwidgets::saveWidget(
  repro_pca,
  file.path(interactive_path, "all_species_pca_repro.html"),
  selfcontained = TRUE
)

```

Examining whether asexual populations occupy more unstable climates than sexual populations. Only using species with multiple sexual and asexual populations. Asexual pops tend to occupy more stable temperature environments, but less stable precipitation environments. We're estimating stability using the method presented by Owens and Guralnick 2019- climateStability: AN R PACKAGE TO ESTIMATE CLIMATE STABILITY FROM TIME-SLICE CLIMATOLOGIES.

```{r cache=TRUE, warning=FALSE, message=FALSE}
### Creating temperature and precipitation stability layers
### Using bio1 (average temp) and bio12 (average precip)
### 2.5 arcmin resolution, already cropped to NZ to speed up computation time


#time slices are calculated as the difference between the midpoints of the two time periods the climate layers were calculated for (e.g. midpoint of LH = (4.2 ka - 0.3 ka) / 2 + 0.3 ka = 2.25, midpoint of MH = (8.326 ka - 4.2 ka) / 2 + 4.2 = 6.263. time_slice = 6.263 - 2.25 = 4.013)
time_slices <- c(2550, 4013, 6037, 1500, 2050, 5150)


precip_deviation <-
  climateStability::deviationThroughTime(variableDirectory = precip_path, timeSlicePeriod = time_slices)

precip_stability <- (1 / precip_deviation)
precip_stability_scaled <- climateStability::rescale0to1(precip_stability)

# write precipitation stability to file
writeRaster(
  precip_stability_scaled,
  filename = file.path(raster_path, "precip_stability_scaled.tif"),
  format = "GTiff"
)


temp_deviation <-
  climateStability::deviationThroughTime(variableDirectory = temp_path, timeSlicePeriod = time_slices)

temp_stability <- (1 / temp_deviation)
temp_stability_scaled <- climateStability::rescale0to1(temp_stability)

# write temperature stability to file
writeRaster(
  temp_stability_scaled,
  filename = file.path(raster_path, "temp_stability_scaled.tif"),
  format = "GTiff"
)

overall_stability_scaled <- precip_stability_scaled * temp_stability_scaled

# write overall stability to file
writeRaster(
  overall_stability_scaled,
  filename = file.path(raster_path, "overall_stability_scaled.tif"),
  format = "GTiff"
)

temp_stability_map <- ggplot() +
  ggspatial::layer_spatial(data = temp_stability_scaled) +
  labs(title = "Temperature stability") +
  scale_fill_viridis_c(na.value = "transparent") +
  theme_minimal()

precip_stability_map <- ggplot() +
  ggspatial::layer_spatial(data = precip_stability_scaled) +
  labs(title = "Precipitation stability") +
  scale_fill_viridis_c(na.value = "transparent") +
  theme_minimal()

overall_stability_map <- ggplot() +
  ggspatial::layer_spatial(data = overall_stability_scaled) +
  labs(title = "Overall stability") +
  scale_fill_viridis_c(na.value = "transparent") +
  theme_minimal()

temp_stability_map
precip_stability_map
overall_stability_map

ggsave("temp_stability.png",
       plot = temp_stability_map,
       device = "png",
       path = map_path,
       dpi = "retina")

ggsave("precip_stability.png",
       plot = precip_stability_map,
       device = "png",
       path = map_path,
       dpi = "retina")

ggsave("overall_stability.png",
       plot = overall_stability_map,
       device = "png",
       path = map_path,
       dpi = "retina")

```



Plot stability across species.
```{r, message=FALSE, warning=FALSE}

# filter for relevant species and asexual reproductive mode
asexual_locs <- loc %>%
  mutate(lat_long = str_c(latitude, longitude)) %>%
  filter(
    reproductive_mode == "asexual",
    species == "horridus" |
      species == "jucundum" |
      species == "hookeri" |
      species == "annulata" |
      species == "ovobessus" |
      species == "huttoni",
    !duplicated(lat_long)
  ) %>%
  dplyr::select(longitude, latitude)

# filter for relevant species and sexual reproductive mode
sexual_locs <- loc %>%
  mutate(lat_long = str_c(latitude, longitude)) %>%
  filter(
    reproductive_mode == "sexual",
    species == "horridus" |
      species == "jucundum" |
      species == "hookeri" |
      species == "annulata" |
      species == "ovobessus" |
      species == "huttoni",
    !duplicated(lat_long)
  ) %>%
  dplyr::select(longitude, latitude)

# extract preciptitation values and bind into a new dataframe
precip_asexual <-
  raster::extract(precip_stability_scaled, asexual_locs) %>%
  enframe(name = NULL, value = "precip_stability_scaled") %>%
  mutate(reproductive_mode = "asexual")

precip_sexual <-
  raster::extract(precip_stability_scaled, sexual_locs) %>%
  enframe(name = NULL, value = "precip_stability_scaled") %>%
  mutate(reproductive_mode = "sexual")

precip_df <- bind_rows(precip_asexual, precip_sexual)

# plot precipitation stability
precip_stability_plot <- ggplot(
  data = precip_df,
  aes(x = reproductive_mode, y = precip_stability_scaled, fill = reproductive_mode)
) +
  geom_violin(width = 0.8) +
  geom_boxplot(width = 0.1,
               color = "gray",
               fill = "transparent") +
  scale_fill_viridis_d(option = "magma") +
  theme_dark()

precip_stability_plot

# extract temperature values and bind into a new data frame
temp_asexual <-
  raster::extract(temp_stability_scaled, asexual_locs) %>%
  enframe(name = NULL, value = "temp_stability_scaled") %>%
  mutate(reproductive_mode = "asexual")

temp_sexual <-
  raster::extract(temp_stability_scaled, sexual_locs) %>%
  enframe(name = NULL, value = "temp_stability_scaled") %>%
  mutate(reproductive_mode = "sexual")

temp_df <- bind_rows(temp_asexual, temp_sexual)

# plot temperature stability
temp_stability_plot <- ggplot(data = temp_df,
       aes(x = reproductive_mode, y = temp_stability_scaled, fill = reproductive_mode)) +
  geom_violin(width = 0.8) +
  geom_boxplot(width = 0.1,
               color = "gray",
               fill = "transparent") +
  scale_fill_viridis_d(option = "magma") +
  theme_dark()

temp_stability_plot

# extract overall stability values and bind into a dataframe
overall_asexual <-
  raster::extract(overall_stability_scaled, asexual_locs) %>%
  enframe(name = NULL, value = "overall_stability_scaled") %>%
  mutate(reproductive_mode = "asexual")

overall_sexual <-
  raster::extract(overall_stability_scaled, sexual_locs) %>%
  enframe(name = NULL, value = "overall_stability_scaled") %>%
  mutate(reproductive_mode = "sexual")

overall_df <- bind_rows(overall_asexual, overall_sexual)

# plot overall stability
overall_stability_plot <- ggplot(
  data = overall_df,
  aes(x = reproductive_mode, y = overall_stability_scaled, fill = reproductive_mode)
) +
  geom_violin(width = 0.8) +
  geom_boxplot(width = 0.1,
               color = "gray",
               fill = "transparent") +
  scale_fill_viridis_d(option = "magma") +
  theme_dark()

overall_stability_plot

ggsave("temp_stability_plot.png",
       plot = temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

ggsave("precip_stability_plot.png",
       plot = precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

ggsave("overall_stability_plot.png",
       plot = overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")
```



## PCA-Species {.tabset}
These are PCAs of environmental space for species within genera. Each climate PCA is of localities for a single genus, colored by species. I'm doing this even for genera with one species, so it's easy to see if certain localities group together. 

### Acanthoxyla
```{r, message=FALSE, warning=FALSE}
#source function to conduct a PCA on individual species
summary_list_acan <- species_pca_fun(loc_clim, "acanthoxyla")
#plot
acan_plot <- plot_clim_pca(summary_list_acan$loc_clim, summary_list_acan$summary_pca, "reproductive_mode")

acan_plot

# save pca plot
htmlwidgets::saveWidget(acan_plot, file.path(interactive_path, "acanthoxyla_pca.html"), selfcontained = TRUE)

#filter localities for the focal genus
acan_loc <- loc %>% 
  filter(genus == "acanthoxyla")
  
#use sourced plot_locs_leaflet script to plot localities
acan_map <- plot_locs_leaflet(acan_loc, "reproductive_mode")

acan_map

# save the map
mapview::mapshot(acan_map, url = file.path(interactive_path, "acan_map.html"), file = file.path(interactive_path,"acan_map.pdf"))
```


```{r}
summary_list_acan$summary_pca
loadings_acan <- summary_list_acan$summary_pca$rotation
knitr::kable(round(loadings_acan[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```


### Argosarchus
```{r message=FALSE, warning=FALSE}
# conduct pca
summary_list_argo <- species_pca_fun(loc_clim, "argosarchus")

# plot
argo_plot <-
  plot_clim_pca(summary_list_argo$loc_clim,
                summary_list_argo$summary_pca,
                factor = "reproductive_mode")
argo_plot

htmlwidgets::saveWidget(argo_plot,
                        file.path(interactive_path, "ahor_pca.html"),
                        selfcontained = TRUE)

#filter localities for the focal genus
argo_loc <- loc %>%
  filter(genus == "argosarchus")

#use sourced plot_locs_leaflet script to plot localities
argo_map <- plot_locs_leaflet(argo_loc, "reproductive_mode")

argo_map

mapview::mapshot(
  argo_map,
  url = file.path(interactive_path, "ahor_map.html"),
  file = file.path(interactive_path, "ahor_map.pdf")
)


```

```{r}
summary_list_argo$summary_pca
loadings_argo <- summary_list_argo$summary_pca$rotation
knitr::kable(round(loadings_argo[, 1:3], 3)) #Table of loading scores for the first 3 PCs. 
```

Now I'm going to to environmental niche factor analysis between sexual and asexual populations within the species.
```{r warning=FALSE, message=FALSE}
#get background env't for the species
ahor_bg_env <- bg_env_crop(argo_loc, 
                           species = "horridus",
                           environment = w, 
                           buffer = 0.5)

#enfa for the sexual species
ahor_sexual_enfa <- enfa_calc_fun(locs = argo_loc, 
                                  species = "horridus", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = ahor_bg_env)

#enfa for the asexual species
ahor_asexual_enfa <- enfa_calc_fun(locs = argo_loc, 
                                   species = "horridus", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = ahor_bg_env)


#plot the marginality scores
ahor_marginality <- marginality_lollipop(sex_marg = ahor_sexual_enfa$m, 
                    asex_marg = ahor_asexual_enfa$m,
                    full_species_name = "Argosarchus horridus")

# write scores to csvs
readr::write_csv(
  ahor_asexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ahor_asexual_marginality_score.csv")
)

readr::write_csv(
  ahor_sexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ahor_sexual_marginality_score.csv")
)

ggsave("ahor_marginality_lollipop.png",
       plot = ahor_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")


```

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. The yellow dot indicates the mean marginality (it's not the value that is on the lollipop plot, so don't let that confuse you). 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations. 
```{r, message=FALSE, warning=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
ahor_asexual_df <- ahor_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ahor_asexual_enfa$pr)

readr::write_csv(ahor_asexual_df, 
                 file.path(spread_path, "ahor_asexual_marginality_df.csv"))

ahor_sexual_df <- ahor_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ahor_sexual_enfa$pr)

readr::write_csv(ahor_sexual_df, 
                 file.path(spread_path, "ahor_sexual_marginality_df.csv"))

#asexual
ahor_enfa_spec_asexual <- enfa_hex_plot(ahor_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ahor_enfa_spec_asexual

ggsave("ahor_enfa_spec_asexual.png",
       plot = ahor_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
ahor_enfa_spec_sexual <- enfa_hex_plot(ahor_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ahor_enfa_spec_sexual

ggsave("ahor_enfa_spec_sexual.png",
       plot = ahor_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
## asexual
hist(ahor_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

# write to file
png(filename = file.path(plot_path, "ahor_asexual_enfa_hist.png"))
hist(ahor_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

## sexual
hist(ahor_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

# write to file
png(filename = file.path(plot_path, "ahor_sexual_enfa_hist.png"))
hist(ahor_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ahor_total_pca <- total_climate_pca_plot(bg_env = ahor_bg_env, locs = argo_loc, genus = "Argosarchus", species = "horridus")

ahor_total_pca

ggsave("ahor_total_pca.png",
       plot = ahor_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")
```


Trying out a repeat of the analyses with reduced environmental space.
Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we're left with BIO6, BIO13, BIO14, BIO16
```{r cache=TRUE}
# PCA of background e-space. Resulting list is a correlation heatmap (cor_heatmap), a tibble of the rasters with correlation > the cutoff (default is 0.75), and a tibble of all pairwise correlations
ahor_pca <- raster_correlation(raster_stack = ahor_bg_env)
ahor_pca$cor_heatmap
ahor_pca$top_cor %>% knitr::kable()

ggsave("ahor_pca_corr.png",
       plot = ahor_pca$cor_heatmap,
       device = "png",
       path = plot_path,
       dpi = "retina")


# write correlation data frame to file
readr::write_csv(ahor_pca$top_cor, file.path(spread_path, "ahor_top_cor.csv"))
```

Repeat the analysis with the reduced data set. The background environment is 0.5 degrees, a ballpark dispersal limitation for all stick insect species in this study.
```{r}
w_ahor <- raster::subset(w, c("bio6", "bio13", "bio14", "bio16"))

#get background env't for the species
ahor_bg_env_subset <- bg_env_crop(argo_loc, 
                           species = "horridus",
                           environment = w_ahor, 
                           buffer = 0.5)

#enfa for the sexual species
ahor_sexual_enfa_subset <- enfa_calc_fun(locs = argo_loc, 
                                  species = "horridus", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = ahor_bg_env_subset)

#enfa for the asexual species
ahor_asexual_enfa_subset <- enfa_calc_fun(locs = argo_loc, 
                                   species = "horridus", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = ahor_bg_env_subset)

# write marginality scores to csv
readr::write_csv(
  ahor_asexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ahor_subset_asexual_marginality_score.csv")
)

readr::write_csv(
  ahor_sexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ahor_subset_sexual_marginality_score.csv")
)

#plot the marginality scores
ahor_subset_marginality <-
  marginality_lollipop(
    sex_marg = ahor_sexual_enfa_subset$m,
    asex_marg = ahor_asexual_enfa_subset$m,
    full_species_name = "Argosarchus horridus"
  )

ahor_subset_marginality

ggsave("ahor_subset_marginality.png",
       plot = ahor_subset_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Visualize with reduced data set
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
ahor_asexual_df_subset <- ahor_asexual_enfa_subset$li %>%
  as_tibble() %>%
  bind_cols(pr = ahor_asexual_enfa_subset$pr)

readr::write_csv(
  ahor_asexual_df_subset,
  file.path(spread_path, "ahor_subset_asexual_marginality_df.csv")
)

ahor_sexual_df_subset <- ahor_sexual_enfa_subset$li %>%
  as_tibble() %>%
  bind_cols(pr = ahor_sexual_enfa_subset$pr)

readr::write_csv(
  ahor_sexual_df_subset,
  file.path(spread_path, "ahor_subset_sexual_marginality_df.csv")
)

#asexual. Jesus these variable names are getting long
ahor_subset_enfa_spec_asexual <-
  enfa_hex_plot(
    ahor_asexual_df_subset,
    marg = Mar,
    spec = Spe1,
    repro_mode = "Asexual"
  )

ahor_subset_enfa_spec_asexual

ggsave(
  "ahor_subset_enfa_spec_asexual.png",
  plot = ahor_subset_enfa_spec_asexual,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

# sexual
ahor_subset_enfa_spec_sexual <-
  enfa_hex_plot(
    ahor_sexual_df_subset,
    marg = Mar,
    spec = Spe1,
    repro_mode = "Sexual"
  )

ahor_subset_enfa_spec_sexual

ggsave(
  "ahor_subset_enfa_spec_sexual.png",
  plot = ahor_subset_enfa_spec_sexual,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

### 2) ENFA histogram
# asexual
hist(ahor_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ahor_subset_asexual_enfa_hist.png"))
hist(ahor_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

# sexual
hist(ahor_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ahor_subset_sexual_enfa_hist.png"))
hist(ahor_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ahor_subset_total_pca <-
  total_climate_pca_plot(
    bg_env = ahor_bg_env_subset,
    locs = argo_loc,
    genus = "Argosarchus",
    species = "horridus"
  )

ahor_subset_total_pca

ggsave(
  "ahor_subset_total_pca.png",
  plot = ahor_subset_total_pca,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(ahor_sexual_enfa, file = file.path(obj_path, "ahor_sexual_enfa.RDS"))
rm(ahor_sexual_enfa)

saveRDS(ahor_asexual_enfa, file = file.path(obj_path, "ahor_asexual_enfa.RDS"))
rm(ahor_asexual_enfa)

saveRDS(ahor_sexual_enfa_subset,
        file = file.path(obj_path, "ahor_subset_sexual_enfa.RDS"))
rm(ahor_sexual_enfa_subset)

saveRDS(ahor_asexual_enfa_subset,
        file = file.path(obj_path, "ahor_subset_asexual_enfa.RDS"))
rm(ahor_asexual_enfa_subset)
```


We're also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations. 
```{r}
argo_locs_asexual <- argo_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

argo_locs_sexual <- argo_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_ahor <- raster::extract(precip_stability_scaled, argo_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_ahor <- raster::extract(precip_stability_scaled, argo_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_ahor <- bind_rows(precip_asexual_ahor, precip_sexual_ahor)

readr::write_csv(precip_df_ahor, 
                 file.path(spread_path, "ahor_precip_stability_df.csv"))

ahor_precip_stability_plot <- ggplot(data = precip_df_ahor, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ahor_precip_stability_plot

ggsave(
  "ahor_precip_stability.png",
  plot = ahor_precip_stability_plot,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

temp_asexual_ahor <- raster::extract(temp_stability_scaled, argo_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_ahor <- raster::extract(temp_stability_scaled, argo_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_ahor <- bind_rows(temp_asexual_ahor, temp_sexual_ahor)

readr::write_csv(temp_df_ahor, 
                 file.path(spread_path, "ahor_temp_stability_df.csv"))

ahor_temp_stability_plot <- ggplot(data = temp_df_ahor, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ahor_temp_stability_plot

ggsave(
  "ahor_temp_stability.png",
  plot = ahor_temp_stability_plot,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

overall_asexual_ahor <- raster::extract(overall_stability_scaled, argo_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_ahor <- raster::extract(overall_stability_scaled, argo_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_ahor <- bind_rows(overall_asexual_ahor, overall_sexual_ahor)

readr::write_csv(overall_df_ahor, 
                 file.path(spread_path, "ahor_overall_stability_df.csv"))


ahor_overall_stability_plot <- ggplot(data = overall_df_ahor, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ahor_overall_stability_plot

ggsave(
  "ahor_overall_stability.png",
  plot = ahor_overall_stability_plot,
  device = "png",
  path = plot_path,
  dpi = "retina"
)

```


Put all output into species-specific subfolders.
```{r results="hide"}
ahor_out_int_path <- file.path(interactive_path, "argosarchus_horridus")
ahor_out_plot_path <- file.path(plot_path, "argosarchus_horridus")
ahor_out_spread_path <- file.path(spread_path, "argosarchus_horridus")
ahor_out_obj_path <- file.path(obj_path, "argosarchus_horridus")

# move interactive
move_to_species(in_path = interactive_path,
                out_path = ahor_out_int_path,
                pattern = "ahor")
# move plots
move_to_species(in_path = plot_path,
                out_path = ahor_out_plot_path,
                pattern = "ahor")

# move spreadsheets
move_to_species(in_path = spread_path,
                out_path = ahor_out_spread_path,
                pattern = "ahor")

# move objects
move_to_species(in_path = obj_path,
                out_path = ahor_out_obj_path,
                pattern = "ahor")
```



### Asteliaphasma
```{r message=FALSE, warning=FALSE}
#pca
summary_list_aste <- species_pca_fun(loc_clim, "asteliaphasma")
#plot
aste_plot <- plot_clim_pca(summary_list_aste$loc_clim, summary_list_aste$summary_pca, factor = "reproductive_mode")
aste_plot

#if selfcontained = TRUE, you can remove the folder that gets added alongside the plot. 
htmlwidgets::saveWidget(aste_plot, file.path(interactive_path, "asteliaphasma_pca.html"), selfcontained = TRUE)

#filter localities for the focal genus
aste_loc <- loc %>% 
  filter(genus == "asteliaphasma")
  
#use sourced plot_locs_leaflet script to plot localities
aste_map <- plot_locs_leaflet(aste_loc, "reproductive_mode")

aste_map

# save the map
mapview::mapshot(aste_map, url = file.path(interactive_path, "aste_map.html"), file = file.path(interactive_path, "aste_map.pdf"))

```



```{r}
summary_list_aste$summary_pca
loadings_aste <- summary_list_aste$summary_pca$rotation
knitr::kable(round(loadings_aste[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```



Now I'm going to to environmental niche factor analysis between sexual and asexual populations within the species.
```{r warning = FALSE, message=FALSE}
#get background env't for the species
ajuc_bg_env <- bg_env_crop(aste_loc, 
                           species = "jucundum",
                           environment = w, 
                           buffer = 0.5)

#enfa for the sexual species
ajuc_sexual_enfa <- enfa_calc_fun(locs = aste_loc, 
                                  species = "jucundum", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = ajuc_bg_env)

#enfa for the asexual species
ajuc_asexual_enfa <- enfa_calc_fun(locs = aste_loc, 
                                   species = "jucundum", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = ajuc_bg_env)


#plot the marginality scores
ajuc_marginality <-  marginality_lollipop(sex_marg = ajuc_sexual_enfa$m, 
                    asex_marg = ajuc_asexual_enfa$m,
                    full_species_name = "Asteliaphasma jucundum")

ajuc_marginality

# write scores to csvs
readr::write_csv(
  ajuc_asexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ajuc_asexual_marginality_score.csv")
)

readr::write_csv(
  ajuc_sexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ajuc_sexual_marginality_score.csv")
)

ggsave("ajuc_marginality_lollipop.png",
       plot = ajuc_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")
```

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations. 
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
ajuc_asexual_df <- ajuc_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_asexual_enfa$pr)

readr::write_csv(ajuc_asexual_df, 
                 file.path(spread_path, "ajuc_asexual_marginality_df.csv"))


ajuc_sexual_df <- ajuc_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_sexual_enfa$pr)

readr::write_csv(ajuc_sexual_df, 
                 file.path(spread_path, "ajuc_sexual_marginality_df.csv"))

#asexual
ajuc_enfa_spec_asexual <- enfa_hex_plot(ajuc_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("ajuc_enfa_spec_asexual.png",
       plot = ajuc_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
ajuc_enfa_spec_sexual <- enfa_hex_plot(ajuc_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("ajuc_enfa_spec_sexual.png",
       plot = ajuc_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(ajuc_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_asexual_enfa_hist.png"))
hist(ajuc_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

# sexual
hist(ajuc_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_sexual_enfa_hist.png"))
hist(ajuc_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ajuc_total_pca <- total_climate_pca_plot(bg_env = ajuc_bg_env, locs = aste_loc, genus = "Asteliophasma", species = "jucundum")

ajuc_total_pca

ggsave("ajuc_total_pca.png",
       plot = ajuc_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")
```


Trying out a repeat of the analyses with reduced environmental space.
Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we're left with BIO5, BIO6, BIO14, BIO17.
```{r}
# PCA of background e-space. Resulting list is a correlation heatmap (cor_heatmap), a tibble of the rasters with correlation > the cutoff (default is 0.75), and a tibble of all pairwise correlations
ajuc_pca <- raster_correlation(raster_stack = ajuc_bg_env)
ajuc_pca$cor_heatmap
ajuc_pca$top_cor %>% knitr::kable()

ggsave("ajuc_pca_corr.png",
       plot = ajuc_pca$cor_heatmap,
       device = "png",
       path = plot_path,
       dpi = "retina")

# write correlation data frame to file
readr::write_csv(ajuc_pca$top_cor, file.path(spread_path, "ajuc_top_cor.csv"))

```


Repeat the analysis with the reduced data set.
```{r}
w_ajuc <- raster::subset(w, c("bio5", "bio6", "bio14", "bio17"))

#get background env't for the species
ajuc_bg_env_subset <- bg_env_crop(aste_loc, 
                           species = "jucundum",
                           environment = w_ajuc, 
                           buffer = 0.5)

#enfa for the sexual species
ajuc_sexual_enfa_subset <- enfa_calc_fun(locs = aste_loc, 
                                  species = "jucundum", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = ajuc_bg_env_subset)

#enfa for the asexual species
ajuc_asexual_enfa_subset <- enfa_calc_fun(locs = aste_loc, 
                                   species = "jucundum", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = ajuc_bg_env_subset)

# write marginality scores to csv
readr::write_csv(
  ajuc_asexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ajuc_subset_asexual_marginality_score.csv")
)

readr::write_csv(
  ajuc_sexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "ajuc_subset_sexual_marginality_score.csv")
)

# plot the marginality scores
ajuc_subset_marginality <-
  marginality_lollipop(
    sex_marg = ajuc_sexual_enfa_subset$m,
    asex_marg = ajuc_asexual_enfa_subset$m,
    full_species_name = "Asteliaphasma jucundum"
  )

ajuc_subset_marginality

ggsave("ajuc_subset_marginality.png",
       plot = ajuc_subset_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")



```


Visualize with the reduced data set.
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
# access the relevant values for plotting
ajuc_asexual_df_subset <- ajuc_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_asexual_enfa_subset$pr)

readr::write_csv(
  ajuc_asexual_df_subset,
  file.path(spread_path, "ajuc_asexual_df_subset.csv")
)


ajuc_sexual_df_subset <- ajuc_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = ajuc_sexual_enfa_subset$pr)

readr::write_csv(
  ajuc_sexual_df_subset,
  file.path(spread_path, "ajuc_sexual_df_subset.csv")
)

# asexual
ajuc_subset_enfa_spec_asexual <- enfa_hex_plot(ajuc_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("ajuc_subset_enfa_spec_asexual.png",
       plot = ajuc_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
ajuc_subset_enfa_spec_sexual <- enfa_hex_plot(ajuc_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("ajuc_subset_enfa_spec_sexual.png",
       plot = ajuc_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(ajuc_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_subset_asexual_enfa_hist.png"))
hist(ajuc_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(ajuc_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "ajuc_subset_sexual_enfa_hist.png"))
hist(ajuc_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
ajuc_subset_total_pca <- total_climate_pca_plot(bg_env = ajuc_bg_env_subset, locs = aste_loc, genus = "Asteliaphasma", species = "jucundum")

ggsave("ajuc_subset_total_pca.png",
       plot = ajuc_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(ajuc_sexual_enfa, file = file.path(obj_path, "ajuc_sexual_enfa.RDS"))
rm(ajuc_sexual_enfa)

saveRDS(ajuc_asexual_enfa, file = file.path(obj_path, "ajuc_asexual_enfa.RDS"))
rm(ajuc_asexual_enfa)

saveRDS(ajuc_sexual_enfa_subset,
        file = file.path(obj_path, "ajuc_subset_sexual_enfa.RDS"))
rm(ajuc_sexual_enfa_subset)

saveRDS(ajuc_asexual_enfa_subset,
        file = file.path(obj_path, "ajuc_subset_asexual_enfa.RDS"))
rm(ajuc_asexual_enfa_subset)
```




We're also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations. 
```{r}
aste_locs_asexual <- aste_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

aste_locs_sexual <- aste_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_ajuc <- raster::extract(precip_stability_scaled, aste_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_ajuc <- raster::extract(precip_stability_scaled, aste_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_ajuc <- bind_rows(precip_asexual_ajuc, precip_sexual_ajuc)

readr::write_csv(precip_df_ajuc, 
                 file.path(spread_path, "ajuc_precip_stability_df.csv"))

ajuc_precip_stability_plot <- ggplot(data = precip_df_ajuc, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ggsave("ajuc_precip_stability.png",
       plot = ajuc_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_ajuc <- raster::extract(temp_stability_scaled, aste_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_ajuc <- raster::extract(temp_stability_scaled, aste_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_ajuc <- bind_rows(temp_asexual_ajuc, temp_sexual_ajuc)

readr::write_csv(temp_df_ajuc, 
                 file.path(spread_path, "ajuc_temp_stability_df.csv"))

ajuc_temp_stability_plot <- ggplot(data = temp_df_ajuc, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ggsave("ajuc_precip_stability.png",
       plot = ajuc_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_ajuc <- raster::extract(overall_stability_scaled, aste_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_ajuc <- raster::extract(overall_stability_scaled, aste_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_ajuc <- bind_rows(overall_asexual_ajuc, overall_sexual_ajuc)

readr::write_csv(overall_df_ajuc, 
                 file.path(spread_path, "ajuc_overall_stability_df.csv"))

ajuc_overall_stability_plot <- ggplot(data = overall_df_ajuc, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

ggsave("ajuc_overall_stability.png",
       plot = ajuc_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Put all output into species-specific subfolders.
```{r results="hide"}
ajuc_out_int_path <- file.path(interactive_path, "asteliaphasma_jucundum")
ajuc_out_plot_path <- file.path(plot_path, "asteliaphasma_jucundum")
ajuc_out_spread_path <- file.path(spread_path, "asteliaphasma_jucundum")
ajuc_out_obj_path <- file.path(obj_path, "asteliaphasma_jucundum")

# move interactive
move_to_species(in_path = interactive_path,
                out_path = ajuc_out_int_path,
                pattern = "ajuc")
# move plots
move_to_species(in_path = plot_path,
                out_path = ajuc_out_plot_path,
                pattern = "ajuc")

# move spreadsheets
move_to_species(in_path = spread_path,
                out_path = ajuc_out_spread_path,
                pattern = "ajuc")

# move objects
move_to_species(in_path = obj_path,
                out_path = ajuc_out_obj_path,
                pattern = "ajuc")
```

### Clitarchus

```{r warning=FALSE, message=FALSE}
summary_list_clita <- species_pca_fun(loc_clim, "Clitarchus")
clita_plot <- plot_clim_pca(summary_list_clita$loc_clim, summary_list_clita$summary_pca, factor = "reproductive_mode")
clita_plot


htmlwidgets::saveWidget(clita_plot, file.path(interactive_path, "Clitarchus_pca.html"), selfcontained = TRUE)

#filter localities for the focal genus
clita_loc <- loc %>% 
  filter(genus == "Clitarchus")
  
#use sourced plot_locs_leaflet script to plot localities
clita_map <- plot_locs_leaflet(clita_loc, "reproductive_mode")

clita_map

# save the map

mapview::mapshot(
  clita_map,
  url = file.path(interactive_path, "clita_map.html"),
  file = paste0(file.path(interactive_path, "clita_map.pdf"))
)

```


```{r}
summary_list_clita$summary_pca
loadings_clita <- summary_list_clita$summary_pca$rotation
knitr::kable(round(loadings_clita[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```


Now I'm going to perform environmental niche factor analysis with sexual and asexual populations within the species.
```{r cache=TRUE, warning=FALSE, message=FALSE}

#get background env't for the species
choo_bg_env <- bg_env_crop(
  clita_loc,
  species = "hookeri",
  environment = w,
  buffer = 0.5
)

#enfa for the sexual species
choo_sexual_enfa <- enfa_calc_fun(
  locs = clita_loc,
  species = "hookeri",
  reproductive_mode = "sexual",
  mask_raster = choo_bg_env
)

#enfa for the asexual species
choo_asexual_enfa <- enfa_calc_fun(
  locs = clita_loc,
  species = "hookeri",
  reproductive_mode = "asexual",
  mask_raster = choo_bg_env
)

# write scores to csvs
readr::write_csv(
  choo_asexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "choo_asexual_marginality_score.csv")
)

readr::write_csv(
  choo_sexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "choo_sexual_marginality_score.csv")
)

#plot the marginality scores
choo_marginality <-
  marginality_lollipop(
    sex_marg = choo_sexual_enfa$m,
    asex_marg = choo_asexual_enfa$m,
    full_species_name = "Clitarchus hookeri"
  )

choo_marginality

ggsave(
  "choo_marginality_lollipop.png",
  plot = choo_marginality,
  device = "png",
  path = plot_path,
  dpi = "retina"
)
```

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations. 
```{r, message=FALSE, warning=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
choo_asexual_df <- choo_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_asexual_enfa$pr)

readr::write_csv(choo_asexual_df, 
                 file.path(spread_path, "choo_asexual_marginality_df.csv"))

choo_sexual_df <- choo_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_sexual_enfa$pr)

readr::write_csv(choo_sexual_df, 
                 file.path(spread_path, "choo_sexual_marginality_df.csv"))

# asexual
choo_enfa_spec_asexual <- enfa_hex_plot(choo_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("choo_enfa_spec_asexual.png",
       plot = choo_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
choo_enfa_spec_sexual <- enfa_hex_plot(choo_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("choo_enfa_spec_sexual.png",
       plot = choo_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(choo_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_asexual_enfa_hist.png"))
hist(choo_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

#sexual
hist(choo_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_sexual_enfa_hist.png"))
hist(choo_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
choo_total_pca <- total_climate_pca_plot(bg_env = choo_bg_env, locs = clita_loc, genus = "Clitarchus", species = "hookeri")

choo_total_pca

ggsave("choo_total_pca.png",
       plot = choo_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Trying out a repeat of the analyses with reduced environmental space.
Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we're left with BIO8, BIO11, BIO15, BIO17. 
```{r}
# PCA of background e-space. Resulting list is a correlation heatmap (cor_heatmap), a tibble of the rasters with correlation > the cutoff (default is 0.75), and a tibble of all pairwise correlations
choo_pca <- raster_correlation(raster_stack = choo_bg_env)
choo_pca$cor_heatmap
choo_pca$top_cor %>% knitr::kable()

ggsave("choo_pca_corr.png",
       plot = choo_pca$cor_heatmap,
       device = "png",
       path = plot_path,
       dpi = "retina")

# write correlation data frame to file
readr::write_csv(choo_pca$top_cor, file.path(spread_path, "choo_top_cor.csv"))

```

Repeat the analysis with the reduced data set.
```{r message=FALSE, warning=FALSE}
w_choo <- raster::subset(w, c("bio8", "bio11", "bio15", "bio17"))

#get background env't for the species
choo_bg_env_subset <- bg_env_crop(clita_loc, 
                           species = "hookeri",
                           environment = w_choo, 
                           buffer = 0.5)

#enfa for the sexual species
choo_sexual_enfa_subset <- enfa_calc_fun(locs = clita_loc, 
                                  species = "hookeri", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = choo_bg_env_subset)

#enfa for the asexual species
choo_asexual_enfa_subset <- enfa_calc_fun(locs = clita_loc, 
                                   species = "hookeri", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = choo_bg_env_subset)

# write marginality scores to csv
readr::write_csv(
  choo_asexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "choo_subset_asexual_marginality_score.csv")
)

readr::write_csv(
  choo_sexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "choo_subset_sexual_marginality_score.csv")
)

# plot the marginality scores
choo_subset_marginality <-
  marginality_lollipop(
    sex_marg = choo_sexual_enfa_subset$m,
    asex_marg = choo_asexual_enfa_subset$m,
    full_species_name = "Clitarchus hookeri"
  )

choo_subset_marginality

ggsave("choo_subset_marginality.png",
       plot = choo_subset_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")

```


Visualize with the reduced data set.
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
# access the relevant values for plotting
choo_asexual_df_subset <- choo_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_asexual_enfa_subset$pr)

readr::write_csv(
  choo_asexual_df_subset,
  file.path(spread_path, "choo_asexual_df_subset.csv")
)


choo_sexual_df_subset <- choo_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = choo_sexual_enfa_subset$pr)

readr::write_csv(
  choo_sexual_df_subset,
  file.path(spread_path, "choo_sexual_df_subset.csv")
)

# asexual
choo_subset_enfa_spec_asexual <- enfa_hex_plot(choo_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("choo_subset_enfa_spec_asexual.png",
       plot = choo_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
choo_subset_enfa_spec_sexual <- enfa_hex_plot(choo_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("choo_subset_enfa_spec_sexual.png",
       plot = choo_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(choo_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_subset_asexual_enfa_hist.png"))
hist(choo_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(choo_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "choo_subset_sexual_enfa_hist.png"))
hist(choo_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
choo_subset_total_pca <- total_climate_pca_plot(bg_env = choo_bg_env_subset, locs = clita_loc, genus = "Clitarchus", species = "hookeri")

choo_subset_total_pca

ggsave("choo_subset_total_pca.png",
       plot = choo_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(choo_sexual_enfa, file = file.path(obj_path, "choo_sexual_enfa.RDS"))
rm(choo_sexual_enfa)

saveRDS(choo_asexual_enfa, file = file.path(obj_path, "choo_asexual_enfa.RDS"))
rm(choo_asexual_enfa)

saveRDS(choo_sexual_enfa_subset,
        file = file.path(obj_path, "choo_subset_sexual_enfa.RDS"))
rm(choo_sexual_enfa_subset)

saveRDS(choo_asexual_enfa_subset,
        file = file.path(obj_path, "choo_subset_asexual_enfa.RDS"))
rm(choo_asexual_enfa_subset)
```


We're also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations. 
```{r warning=FALSE, message=FALSE}
clita_locs_asexual <- clita_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

clita_locs_sexual <- clita_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_choo <- raster::extract(precip_stability_scaled, clita_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_choo <- raster::extract(precip_stability_scaled, clita_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_choo <- bind_rows(precip_asexual_choo, precip_sexual_choo)

readr::write_csv(precip_df_choo, 
                 file.path(spread_path, "choo_precip_stability_df.csv"))

choo_precip_stability_plot <- ggplot(data = precip_df_choo, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

choo_precip_stability_plot

ggsave("choo_precip_stability.png",
       plot = choo_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_choo <- raster::extract(temp_stability_scaled, clita_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_choo <- raster::extract(temp_stability_scaled, clita_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_choo <- bind_rows(temp_asexual_choo, temp_sexual_choo)

readr::write_csv(temp_df_choo, 
                 file.path(spread_path, "choo_temp_stability_df.csv"))

choo_temp_stability_plot <- ggplot(data = temp_df_choo, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

choo_temp_stability_plot

ggsave("choo_precip_stability.png",
       plot = choo_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_choo <- raster::extract(overall_stability_scaled, clita_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_choo <- raster::extract(overall_stability_scaled, clita_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_choo <- bind_rows(overall_asexual_choo, overall_sexual_choo)

readr::write_csv(overall_df_choo, 
                 file.path(spread_path, "choo_overall_stability_df.csv"))

choo_overall_stability_plot <- ggplot(data = overall_df_choo, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

choo_overall_stability_plot

ggsave("choo_overall_stability.png",
       plot = choo_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")
```

Put all output into species-specific subfolders.
```{r results="hide"}
choo_out_int_path <- file.path(interactive_path, "clitarchus_hookeri")
choo_out_plot_path <- file.path(plot_path, "clitarchus_hookeri")
choo_out_spread_path <- file.path(spread_path, "clitarchus_hookeri")
choo_out_obj_path <- file.path(obj_path, "clitarchus_hookeri")

# move interactive
move_to_species(in_path = interactive_path,
                out_path = choo_out_int_path,
                pattern = "choo")
# move plots
move_to_species(in_path = plot_path,
                out_path = choo_out_plot_path,
                pattern = "choo")

# move spreadsheets
move_to_species(in_path = spread_path,
                out_path = choo_out_spread_path,
                pattern = "choo")

# move objects
move_to_species(in_path = obj_path,
                out_path = choo_out_obj_path,
                pattern = "choo")
```

### Micrarchus
```{r warning=FALSE, message=FALSE}
summary_list_micra <- species_pca_fun(loc_clim, "micrarchus")
micra_plot <- plot_clim_pca(summary_list_micra$loc_clim, summary_list_micra$summary_pca, factor = "reproductive_mode")
micra_plot

# if selfcontained = TRUE, you can remove the folder that gets added alongside the plot.
htmlwidgets::saveWidget(micra_plot,
                        file.path(interactive_path, "micrarchus_pca.html"),
                        selfcontained = TRUE)

#filter localities for the focal genus
micra_loc <- loc %>% 
  filter(genus == "micrarchus")
  
#use sourced plot_locs_leaflet script to plot localities
micra_map <- plot_locs_leaflet(micra_loc, "reproductive_mode")

micra_map

# save the map
mapview::mapshot(micra_map, url = file.path(interactive_path, "micra_map.html"), file = file.path(interactive_path, "micra_map.pdf"))
```


```{r}
summary_list_micra$summary_pca
loadings_micra <- summary_list_micra$summary_pca$rotation
knitr::kable(round(loadings_micra[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```

### Niveaphasma

```{r, warning=FALSE, message=TRUE}
summary_list_nive <- species_pca_fun(loc_clim, "niveaphasma")
nive_plot <- plot_clim_pca(summary_list_nive$loc_clim, summary_list_nive$summary_pca, factor = "reproductive_mode")

nive_plot

# save the plot 
htmlwidgets::saveWidget(nive_plot, file.path(interactive_path, "niveaphasma_pca.html"), selfcontained = TRUE)

#filter localities for the focal genus
nive_loc <- loc %>% 
  filter(genus == "niveaphasma")
  
#use sourced plot_locs_leaflet script to plot localities
nive_map <- plot_locs_leaflet(nive_loc, "reproductive_mode")

nive_map

# save the map
mapview::mapshot(nive_map, url = file.path(interactive_path, "nive_map.html"), file = file.path(interactive_path, "nive_map.pdf"))

```

```{r}
summary_list_nive$summary_pca
loadings_nive <- summary_list_nive$summary_pca$rotation
knitr::kable(round(loadings_nive[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```


Now I'm going to perform environmental niche factor analysis with sexual and asexual populations within the species.
```{r cache=TRUE, warning=FALSE, message=FALSE}
# get background env't for the species
nive_bg_env <- bg_env_crop(
  nive_loc,
  species = "annulata",
  environment = w,
  buffer = 0.5
)

#enfa for the sexual species
nive_sexual_enfa <- enfa_calc_fun(
  locs = nive_loc,
  species = "annulata",
  reproductive_mode = "sexual",
  mask_raster = nive_bg_env
)

#enfa for the asexual species
nive_asexual_enfa <- enfa_calc_fun(
  locs = nive_loc,
  species = "annulata",
  reproductive_mode = "asexual",
  mask_raster = nive_bg_env
)

# write scores to csvs
readr::write_csv(
  nive_asexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "nive_asexual_marginality_score.csv")
)

readr::write_csv(
  nive_sexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "nive_sexual_marginality_score.csv")
)

#plot the marginality scores
nive_marginality <-
  marginality_lollipop(
    sex_marg = nive_sexual_enfa$m,
    asex_marg = nive_asexual_enfa$m,
    full_species_name = "Niveaphasma annulata"
  )

nive_marginality

ggsave(
  "nive_marginality_lollipop.png",
  plot = nive_marginality,
  device = "png",
  path = plot_path,
  dpi = "retina"
)
```



A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations. 
```{r, message=FALSE, warning=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
nive_asexual_df <- nive_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_asexual_enfa$pr)

readr::write_csv(nive_asexual_df, 
                 file.path(spread_path, "nive_asexual_marginality_df.csv"))

nive_sexual_df <- nive_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_sexual_enfa$pr)

readr::write_csv(nive_sexual_df, 
                 file.path(spread_path, "nive_sexual_marginality_df.csv"))

# asexual
nive_enfa_spec_asexual <- enfa_hex_plot(nive_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("nive_enfa_spec_asexual.png",
       plot = nive_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
nive_enfa_spec_sexual <- enfa_hex_plot(nive_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("nive_enfa_spec_sexual.png",
       plot = nive_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(nive_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_asexual_enfa_hist.png"))
hist(nive_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

#sexual
hist(nive_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_sexual_enfa_hist.png"))
hist(nive_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
nive_total_pca <- total_climate_pca_plot(bg_env = nive_bg_env, locs = nive_loc, genus = "Niveaphasma", species = "annulata")

nive_total_pca

ggsave("nive_total_pca.png",
       plot = nive_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

```


Trying out a repeat of the analyses with reduced environmental space.
Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we're left with BIO4, BIO8, BIO9, BIO11, BIO15, BIO17
```{r message=FALSE, warning=FALSE}
# PCA of background e-space. Resulting list is a correlation heatmap (cor_heatmap), a tibble of the rasters with correlation > the cutoff (default is 0.75), and a tibble of all pairwise correlations
nive_pca <- raster_correlation(raster_stack = nive_bg_env)
nive_pca$cor_heatmap
nive_pca$top_cor %>% knitr::kable()

ggsave("nive_pca_corr.png",
       plot = nive_pca$cor_heatmap,
       device = "png",
       path = plot_path,
       dpi = "retina")

# write correlation data frame to file
readr::write_csv(nive_pca$top_cor, file.path(spread_path, "nive_top_cor.csv"))

```

Repeat the analysis with the reduced data set.
```{r message=FALSE, warning=FALSE}
w_nive <- raster::subset(w, c("bio4", "bio8", "bio9", "bio11", "bio15", "bio17"))

#get background env't for the species
nive_bg_env_subset <- bg_env_crop(nive_loc, 
                           species = "annulata",
                           environment = w_nive, 
                           buffer = 0.5)

#enfa for the sexual species
nive_sexual_enfa_subset <- enfa_calc_fun(locs = nive_loc, 
                                  species = "annulata", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = nive_bg_env_subset)

#enfa for the asexual species
nive_asexual_enfa_subset <- enfa_calc_fun(locs = nive_loc, 
                                   species = "annulata", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = nive_bg_env_subset)

# write marginality scores to csv
readr::write_csv(
  nive_asexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "nive_subset_asexual_marginality_score.csv")
)

readr::write_csv(
  nive_sexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "nive_subset_sexual_marginality_score.csv")
)

# plot the marginality scores
nive_subset_marginality <-
  marginality_lollipop(
    sex_marg = nive_sexual_enfa_subset$m,
    asex_marg = nive_asexual_enfa_subset$m,
    full_species_name = "Niveaphasma annulata"
  )

nive_subset_marginality

ggsave("nive_subset_marginality.png",
       plot = nive_subset_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Visualize with the reduced data set.
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
# access the relevant values for plotting
nive_asexual_df_subset <- nive_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_asexual_enfa_subset$pr)

readr::write_csv(
  nive_asexual_df_subset,
  file.path(spread_path, "nive_asexual_df_subset.csv")
)


nive_sexual_df_subset <- nive_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = nive_sexual_enfa_subset$pr)

readr::write_csv(
  nive_sexual_df_subset,
  file.path(spread_path, "nive_sexual_df_subset.csv")
)

# asexual
nive_subset_enfa_spec_asexual <- enfa_hex_plot(nive_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("nive_subset_enfa_spec_asexual.png",
       plot = nive_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
nive_subset_enfa_spec_sexual <- enfa_hex_plot(nive_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("nive_subset_enfa_spec_sexual.png",
       plot = nive_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(nive_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_subset_asexual_enfa_hist.png"))
hist(nive_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(nive_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "nive_subset_sexual_enfa_hist.png"))
hist(nive_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
nive_subset_total_pca <- total_climate_pca_plot(bg_env = nive_bg_env_subset, locs = nive_loc, genus = "Niveaphasma", species = "annulata")

nive_subset_total_pca

ggsave("nive_subset_total_pca.png",
       plot = nive_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(nive_sexual_enfa, file = file.path(obj_path, "nive_sexual_enfa.RDS"))
rm(nive_sexual_enfa)

saveRDS(nive_asexual_enfa, file = file.path(obj_path, "nive_asexual_enfa.RDS"))
rm(nive_asexual_enfa)

saveRDS(nive_sexual_enfa_subset,
        file = file.path(obj_path, "nive_subset_sexual_enfa.RDS"))
rm(nive_sexual_enfa_subset)

saveRDS(nive_asexual_enfa_subset,
        file = file.path(obj_path, "nive_subset_asexual_enfa.RDS"))
rm(nive_asexual_enfa_subset)
```

We're also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations. 
```{r warning=FALSE, message=FALSE}
nive_locs_asexual <- nive_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

nive_locs_sexual <- nive_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_nive <- raster::extract(precip_stability_scaled, nive_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_nive <- raster::extract(precip_stability_scaled, nive_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_nive <- bind_rows(precip_asexual_nive, precip_sexual_nive)

readr::write_csv(precip_df_nive, 
                 file.path(spread_path, "nive_precip_stability_df.csv"))

nive_precip_stability_plot <- ggplot(data = precip_df_nive, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

nive_precip_stability_plot

ggsave("nive_precip_stability.png",
       plot = nive_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_nive <- raster::extract(temp_stability_scaled, nive_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_nive <- raster::extract(temp_stability_scaled, nive_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_nive <- bind_rows(temp_asexual_nive, temp_sexual_nive)

readr::write_csv(temp_df_nive, 
                 file.path(spread_path, "nive_temp_stability_df.csv"))

nive_temp_stability_plot <- ggplot(data = temp_df_nive, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

nive_temp_stability_plot

ggsave("nive_precip_stability.png",
       plot = nive_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_nive <- raster::extract(overall_stability_scaled, nive_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_nive <- raster::extract(overall_stability_scaled, nive_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_nive <- bind_rows(overall_asexual_nive, overall_sexual_nive)

readr::write_csv(overall_df_nive, 
                 file.path(spread_path, "nive_overall_stability_df.csv"))

nive_overall_stability_plot <- ggplot(data = overall_df_nive, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

nive_overall_stability_plot

ggsave("nive_overall_stability.png",
       plot = nive_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")
```

Put all output into species-specific subfolders.
```{r results="hide"}
nive_out_int_path <- file.path(interactive_path, "niveaphasma_annulata")
nive_out_plot_path <- file.path(plot_path, "niveaphasma_annulata")
nive_out_spread_path <- file.path(spread_path, "niveaphasma_annulata")
nive_out_obj_path <- file.path(obj_path, "niveaphasma_annulata")

# move interactive
move_to_species(in_path = interactive_path,
                out_path = nive_out_int_path,
                pattern = "nive")
# move plots
move_to_species(in_path = plot_path,
                out_path = nive_out_plot_path,
                pattern = "nive")

# move spreadsheets
move_to_species(in_path = spread_path,
                out_path = nive_out_spread_path,
                pattern = "nive")

# move objects
move_to_species(in_path = obj_path,
                out_path = nive_out_obj_path,
                pattern = "nive")
```


### Spinotectarchus

```{r, warning=FALSE, message=TRUE}
summary_list_spin <- species_pca_fun(loc_clim, "spinotectarchus")
spin_plot <- plot_clim_pca(summary_list_spin$loc_clim, summary_list_spin$summary_pca, factor = "reproductive_mode")

spin_plot

# save the plot 
htmlwidgets::saveWidget(spin_plot, file.path(interactive_path, "spinotectarchus_pca.html"), selfcontained = TRUE)

#filter localities for the focal genus
spin_loc <- loc %>% 
  filter(genus == "spinotectarchus")
  
#use sourced plot_locs_leaflet script to plot localities
spin_map <- plot_locs_leaflet(spin_loc, "reproductive_mode")

spin_map

# save the map
mapview::mapshot(spin_map, url = file.path(interactive_path, "spin_map.html"), file = file.path(interactive_path, "spin_map.pdf"))

```

```{r}
summary_list_spin$summary_pca
loadings_spin <- summary_list_spin$summary_pca$rotation
knitr::kable(round(loadings_spin[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```


### Tectarchus
```{r, warning=FALSE, message=TRUE}
summary_list_tect <- species_pca_fun(loc_clim, "tectarchus")
tect_plot <- plot_clim_pca(summary_list_tect$loc_clim, summary_list_tect$summary_pca, factor = "reproductive_mode")

tect_plot

# save the plot 
htmlwidgets::saveWidget(tect_plot, file.path(interactive_path, "tectarchus_pca.html"), selfcontained = TRUE)

#filter localities for the focal genus
tect_loc <- loc %>% 
  filter(genus == "tectarchus")
  
#use sourced plot_locs_leaflet script to plot localities
tect_map <- plot_locs_leaflet(tect_loc, "reproductive_mode")

tect_map

# save the map
mapview::mapshot(tect_map, url = file.path(interactive_path, "tect_map.html"), file = file.path(interactive_path, "tect_map.pdf"))

```

```{r}
summary_list_tect$summary_pca
loadings_tect <- summary_list_tect$summary_pca$rotation
knitr::kable(round(loadings_tect[,1:3],3)) #Table of loading scores for the first 3 PCs. 
```

#### Tectarchus ovobessus
Now I'm going to perform environmental niche factor analysis with sexual and asexual populations within the species.
```{r cache=TRUE, warning=FALSE, message=FALSE}
# get background env't for the species
tect_ovo_bg_env <- bg_env_crop(
  tect_loc,
  species = "ovobessus",
  environment = w,
  buffer = 0.5
)

#enfa for the sexual species
tect_ovo_sexual_enfa <- enfa_calc_fun(
  locs = tect_loc,
  species = "ovobessus",
  reproductive_mode = "sexual",
  mask_raster = tect_ovo_bg_env
)

#enfa for the asexual species
tect_ovo_asexual_enfa <- enfa_calc_fun(
  locs = tect_loc,
  species = "ovobessus",
  reproductive_mode = "asexual",
  mask_raster = tect_ovo_bg_env
)

# write scores to csvs
readr::write_csv(
  tect_ovo_asexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_ovo_asexual_marginality_score.csv")
)

readr::write_csv(
  tect_ovo_sexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_ovo_sexual_marginality_score.csv")
)

#plot the marginality scores
tect_ovo_marginality <-
  marginality_lollipop(
    sex_marg = tect_ovo_sexual_enfa$m,
    asex_marg = tect_ovo_asexual_enfa$m,
    full_species_name = "Tectarchus ovobessus"
  )

tect_ovo_marginality

ggsave(
  "tect_ovo_marginality_lollipop.png",
  plot = tect_ovo_marginality,
  device = "png",
  path = plot_path,
  dpi = "retina"
)
```


A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations. 
```{r, message=FALSE, warning=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
tect_ovo_asexual_df <- tect_ovo_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_ovo_asexual_enfa$pr)

readr::write_csv(tect_ovo_asexual_df, 
                 file.path(spread_path, "tect_ovo_asexual_marginality_df.csv"))

tect_ovo_sexual_df <- tect_ovo_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_ovo_sexual_enfa$pr)

readr::write_csv(tect_ovo_sexual_df, 
                 file.path(spread_path, "tect_ovo_sexual_marginality_df.csv"))

# asexual
tect_ovo_enfa_spec_asexual <- enfa_hex_plot(tect_ovo_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("tect_ovo_enfa_spec_asexual.png",
       plot = tect_ovo_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
tect_ovo_enfa_spec_sexual <- enfa_hex_plot(tect_ovo_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("tect_ovo_enfa_spec_sexual.png",
       plot = tect_ovo_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(tect_ovo_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_ovo_asexual_enfa_hist.png"))
hist(tect_ovo_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

#sexual
hist(tect_ovo_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_ovo_sexual_enfa_hist.png"))
hist(tect_ovo_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
tect_ovo_total_pca <- total_climate_pca_plot(bg_env = tect_ovo_bg_env, locs = tect_loc, genus = "Tectarchus", species = "ovobessus")

tect_ovo_total_pca

ggsave("tect_ovo_total_pca.png",
       plot = tect_ovo_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Trying out a repeat of the analyses with reduced environmental space.
Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we're left with BIO4, BIO8, BIO11, BIO15, BIO17
```{r message=FALSE, warning=FALSE}
# PCA of background e-space. Resulting list is a correlation heatmap (cor_heatmap), a tibble of the rasters with correlation > the cutoff (default is 0.75), and a tibble of all pairwise correlations
tect_ovo_pca <- raster_correlation(raster_stack = tect_ovo_bg_env)
tect_ovo_pca$cor_heatmap
tect_ovo_pca$top_cor %>% knitr::kable()

ggsave("tect_ovo_pca_corr.png",
       plot = tect_ovo_pca$cor_heatmap,
       device = "png",
       path = plot_path,
       dpi = "retina")

# write correlation data frame to file
readr::write_csv(tect_ovo_pca$top_cor, file.path(spread_path, "tect_ovo_top_cor.csv"))

```

Repeat the analysis with the reduced data set.
```{r message=FALSE, warning=FALSE}
w_tect_ovo <- raster::subset(w, c("bio4", "bio8", "bio11", "bio15", "bio17"))

#get background env't for the species
tect_ovo_bg_env_subset <- bg_env_crop(tect_loc, 
                           species = "ovobessus",
                           environment = w_tect_ovo, 
                           buffer = 0.5)

#enfa for the sexual species
tect_ovo_sexual_enfa_subset <- enfa_calc_fun(locs = tect_loc, 
                                  species = "ovobessus", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = tect_ovo_bg_env_subset)

#enfa for the asexual species
tect_ovo_asexual_enfa_subset <- enfa_calc_fun(locs = tect_loc, 
                                   species = "ovobessus", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = tect_ovo_bg_env_subset)

# write marginality scores to csv
readr::write_csv(
  tect_ovo_asexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_ovo_subset_asexual_marginality_score.csv")
)

readr::write_csv(
  tect_ovo_sexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_ovo_subset_sexual_marginality_score.csv")
)

# plot the marginality scores
tect_ovo_subset_marginality <-
  marginality_lollipop(
    sex_marg = tect_ovo_sexual_enfa_subset$m,
    asex_marg = tect_ovo_asexual_enfa_subset$m,
    full_species_name = "Tectarchus ovobessus"
  )

tect_ovo_subset_marginality

ggsave("tect_ovo_subset_marginality.png",
       plot = tect_ovo_subset_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Visualize with the reduced data set.
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
# access the relevant values for plotting
tect_ovo_asexual_df_subset <- tect_ovo_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_ovo_asexual_enfa_subset$pr)

readr::write_csv(
  tect_ovo_asexual_df_subset,
  file.path(spread_path, "tect_ovo_asexual_df_subset.csv")
)


tect_ovo_sexual_df_subset <- tect_ovo_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_ovo_sexual_enfa_subset$pr)

readr::write_csv(
  tect_ovo_sexual_df_subset,
  file.path(spread_path, "tect_ovo_sexual_df_subset.csv")
)

# asexual
tect_ovo_subset_enfa_spec_asexual <- enfa_hex_plot(tect_ovo_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("tect_ovo_subset_enfa_spec_asexual.png",
       plot = tect_ovo_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
tect_ovo_subset_enfa_spec_sexual <- enfa_hex_plot(tect_ovo_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("tect_ovo_subset_enfa_spec_sexual.png",
       plot = tect_ovo_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(tect_ovo_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_ovo_subset_asexual_enfa_hist.png"))
hist(tect_ovo_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(tect_ovo_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_ovo_subset_sexual_enfa_hist.png"))
hist(tect_ovo_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
tect_ovo_subset_total_pca <- total_climate_pca_plot(bg_env = tect_ovo_bg_env_subset, locs = tect_loc, genus = "Tectarchus", species = "ovobessus")

tect_ovo_subset_total_pca

ggsave("tect_ovo_subset_total_pca.png",
       plot = tect_ovo_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(tect_ovo_sexual_enfa, file = file.path(obj_path, "tect_ovo_sexual_enfa.RDS"))
rm(tect_ovo_sexual_enfa)

saveRDS(tect_ovo_asexual_enfa, file = file.path(obj_path, "tect_ovo_asexual_enfa.RDS"))
rm(tect_ovo_asexual_enfa)

saveRDS(tect_ovo_sexual_enfa_subset,
        file = file.path(obj_path, "tect_ovo_subset_sexual_enfa.RDS"))
rm(tect_ovo_sexual_enfa_subset)

saveRDS(tect_ovo_asexual_enfa_subset,
        file = file.path(obj_path, "tect_ovo_subset_asexual_enfa.RDS"))
rm(tect_ovo_asexual_enfa_subset)
```

We're also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations. 
```{r warning=FALSE, message=FALSE}
tect_ovo_locs_asexual <- tect_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         species == "ovobessus",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

tect_ovo_locs_sexual <- tect_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         species == "ovobessus",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_tect_ovo <- raster::extract(precip_stability_scaled, tect_ovo_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_tect_ovo <- raster::extract(precip_stability_scaled, tect_ovo_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_tect_ovo <- bind_rows(precip_asexual_tect_ovo, precip_sexual_tect_ovo)

readr::write_csv(precip_df_tect_ovo, 
                 file.path(spread_path, "tect_ovo_precip_stability_df.csv"))

tect_ovo_precip_stability_plot <- ggplot(data = precip_df_tect_ovo, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

tect_ovo_precip_stability_plot

ggsave("tect_ovo_precip_stability.png",
       plot = tect_ovo_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_tect_ovo <- raster::extract(temp_stability_scaled, tect_ovo_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_tect_ovo <- raster::extract(temp_stability_scaled, tect_ovo_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_tect_ovo <- bind_rows(temp_asexual_tect_ovo, temp_sexual_tect_ovo)

readr::write_csv(temp_df_tect_ovo, 
                 file.path(spread_path, "tect_ovo_temp_stability_df.csv"))

tect_ovo_temp_stability_plot <- ggplot(data = temp_df_tect_ovo, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

tect_ovo_temp_stability_plot

ggsave("tect_ovo_precip_stability.png",
       plot = tect_ovo_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_tect_ovo <- raster::extract(overall_stability_scaled, tect_ovo_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_tect_ovo <- raster::extract(overall_stability_scaled, tect_ovo_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_tect_ovo <- bind_rows(overall_asexual_tect_ovo, overall_sexual_tect_ovo)

readr::write_csv(overall_df_tect_ovo, 
                 file.path(spread_path, "tect_ovo_overall_stability_df.csv"))

tect_ovo_overall_stability_plot <- ggplot(data = overall_df_tect_ovo, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

tect_ovo_overall_stability_plot

ggsave("tect_ovo_overall_stability.png",
       plot = tect_ovo_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")
```


Put all output into species-specific subfolders.
```{r results="hide"}
tect_ovo_out_int_path <- file.path(interactive_path, "tectarchus_ovobessus")
tect_ovo_out_plot_path <- file.path(plot_path, "tectarchus_ovobessus")
tect_ovo_out_spread_path <- file.path(spread_path, "tectarchus_ovobessus")
tect_ovo_out_obj_path <- file.path(obj_path, "tectarchus_ovobessus")

# move interactive
move_to_species(in_path = interactive_path,
                out_path = tect_ovo_out_int_path,
                pattern = "tect_ovo")
# move plots
move_to_species(in_path = plot_path,
                out_path = tect_ovo_out_plot_path,
                pattern = "tect_ovo")

# move spreadsheets
move_to_species(in_path = spread_path,
                out_path = tect_ovo_out_spread_path,
                pattern = "tect_ovo")

# move objects
move_to_species(in_path = obj_path,
                out_path = tect_ovo_out_obj_path,
                pattern = "tect_ovo")
```


#### Tectarchus huttoni

Now I'm going to perform environmental niche factor analysis with sexual and asexual populations within the species.
```{r cache=TRUE, warning=FALSE, message=FALSE}
# get background env't for the species
tect_hutt_bg_env <- bg_env_crop(
  tect_loc,
  species = "huttoni",
  environment = w,
  buffer = 0.5
)

#enfa for the sexual species
tect_hutt_sexual_enfa <- enfa_calc_fun(
  locs = tect_loc,
  species = "huttoni",
  reproductive_mode = "sexual",
  mask_raster = tect_hutt_bg_env
)

#enfa for the asexual species
tect_hutt_asexual_enfa <- enfa_calc_fun(
  locs = tect_loc,
  species = "huttoni",
  reproductive_mode = "asexual",
  mask_raster = tect_hutt_bg_env
)

# write scores to csvs
readr::write_csv(
  tect_hutt_asexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_hutt_asexual_marginality_score.csv")
)

readr::write_csv(
  tect_hutt_sexual_enfa$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_hutt_sexual_marginality_score.csv")
)

#plot the marginality scores
tect_hutt_marginality <-
  marginality_lollipop(
    sex_marg = tect_hutt_sexual_enfa$m,
    asex_marg = tect_hutt_asexual_enfa$m,
    full_species_name = "Tectarchus huttoni"
  )

tect_hutt_marginality

ggsave(
  "tect_hutt_marginality_lollipop.png",
  plot = tect_hutt_marginality,
  device = "png",
  path = plot_path,
  dpi = "retina"
)
```

A couple different ways to visualize the environmental variation. 1) Scatterplot visualizations of marginality vs axis 1 of the specialization with the labels removed (they make things indiscernable). Red = occupied e-space. Gray = Background e-space. 2) ENFA histogram visualizations of marginality and specialization axes. 3) PCA of total e-space with colors corresponding to sexual vs. asexual populations. 
```{r, message=FALSE, warning=FALSE}
### 1) ENFA scatterplot
#access the relevant values for plotting
tect_hutt_asexual_df <- tect_hutt_asexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_hutt_asexual_enfa$pr)

readr::write_csv(tect_hutt_asexual_df, 
                 file.path(spread_path, "tect_hutt_asexual_marginality_df.csv"))

tect_hutt_sexual_df <- tect_hutt_sexual_enfa$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_hutt_sexual_enfa$pr)

readr::write_csv(tect_hutt_sexual_df, 
                 file.path(spread_path, "tect_hutt_sexual_marginality_df.csv"))

# asexual
tect_hutt_enfa_spec_asexual <- enfa_hex_plot(tect_hutt_asexual_df, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("tect_hutt_enfa_spec_asexual.png",
       plot = tect_hutt_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

#sexual
tect_hutt_enfa_spec_sexual <- enfa_hex_plot(tect_hutt_sexual_df, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("tect_hutt_enfa_spec_sexual.png",
       plot = tect_hutt_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
#asexual
hist(tect_hutt_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_hutt_asexual_enfa_hist.png"))
hist(tect_hutt_asexual_enfa)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()

#sexual
hist(tect_hutt_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_hutt_sexual_enfa_hist.png"))
hist(tect_hutt_sexual_enfa)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
tect_hutt_total_pca <- total_climate_pca_plot(bg_env = tect_hutt_bg_env, locs = tect_loc, genus = "Tectarchus", species = "huttoni")

tect_hutt_total_pca

ggsave("tect_hutt_total_pca.png",
       plot = tect_hutt_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Trying out a repeat of the analyses with reduced environmental space.
Prioritizing variables that will limit their distribution (i.e. variables that represent the extremes). After correlation analysis, we're left with BIO4, BIO8, BIO11, BIO15, BIO17
```{r message=FALSE, warning=FALSE}
# PCA of background e-space. Resulting list is a correlation heatmap (cor_heatmap), a tibble of the rasters with correlation > the cutoff (default is 0.75), and a tibble of all pairwise correlations
tect_hutt_pca <- raster_correlation(raster_stack = tect_hutt_bg_env)
tect_hutt_pca$cor_heatmap
tect_hutt_pca$top_cor %>% knitr::kable()

ggsave("tect_hutt_pca_corr.png",
       plot = tect_hutt_pca$cor_heatmap,
       device = "png",
       path = plot_path,
       dpi = "retina")

# write correlation data frame to file
readr::write_csv(tect_hutt_pca$top_cor, file.path(spread_path, "tect_hutt_top_cor.csv"))

```

Repeat the analysis with the reduced data set.
```{r message=FALSE, warning=FALSE}
w_tect_hutt <- raster::subset(w, c("bio4", "bio8", "bio11", "bio15", "bio17"))

#get background env't for the species
tect_hutt_bg_env_subset <- bg_env_crop(tect_loc, 
                           species = "huttoni",
                           environment = w_tect_hutt, 
                           buffer = 0.5)

#enfa for the sexual species
tect_hutt_sexual_enfa_subset <- enfa_calc_fun(locs = tect_loc, 
                                  species = "huttoni", 
                                  reproductive_mode = "sexual", 
                                  mask_raster = tect_hutt_bg_env_subset)

#enfa for the asexual species
tect_hutt_asexual_enfa_subset <- enfa_calc_fun(locs = tect_loc, 
                                   species = "huttoni", 
                                   reproductive_mode = "asexual", 
                                   mask_raster = tect_hutt_bg_env_subset)

# write marginality scores to csv
readr::write_csv(
  tect_hutt_asexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_hutt_subset_asexual_marginality_score.csv")
)

readr::write_csv(
  tect_hutt_sexual_enfa_subset$m %>% enframe(name = NULL, value = "marginality"),
  file.path(spread_path, "tect_hutt_subset_sexual_marginality_score.csv")
)

# plot the marginality scores
tect_hutt_subset_marginality <-
  marginality_lollipop(
    sex_marg = tect_hutt_sexual_enfa_subset$m,
    asex_marg = tect_hutt_asexual_enfa_subset$m,
    full_species_name = "Tectarchus huttoni"
  )

tect_hutt_subset_marginality

ggsave("tect_hutt_subset_marginality.png",
       plot = tect_hutt_subset_marginality,
       device = "png",
       path = plot_path,
       dpi = "retina")

```

Visualize with the reduced data set.
```{r warning=FALSE, message=FALSE}
### 1) ENFA scatterplot
# access the relevant values for plotting
tect_hutt_asexual_df_subset <- tect_hutt_asexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_hutt_asexual_enfa_subset$pr)

readr::write_csv(
  tect_hutt_asexual_df_subset,
  file.path(spread_path, "tect_hutt_asexual_df_subset.csv")
)


tect_hutt_sexual_df_subset <- tect_hutt_sexual_enfa_subset$li %>% 
  as_tibble() %>% 
  bind_cols(pr = tect_hutt_sexual_enfa_subset$pr)

readr::write_csv(
  tect_hutt_sexual_df_subset,
  file.path(spread_path, "tect_hutt_sexual_df_subset.csv")
)

# asexual
tect_hutt_subset_enfa_spec_asexual <- enfa_hex_plot(tect_hutt_asexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Asexual")

ggsave("tect_hutt_subset_enfa_spec_asexual.png",
       plot = tect_hutt_subset_enfa_spec_asexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

# sexual
tect_hutt_subset_enfa_spec_sexual <- enfa_hex_plot(tect_hutt_sexual_df_subset, marg = Mar, spec = Spe1, repro_mode = "Sexual")

ggsave("tect_hutt_subset_enfa_spec_sexual.png",
       plot = tect_hutt_subset_enfa_spec_sexual,
       device = "png",
       path = plot_path,
       dpi = "retina")

### 2) ENFA histogram
# asexual
hist(tect_hutt_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_hutt_subset_asexual_enfa_hist.png"))
hist(tect_hutt_asexual_enfa_subset)
title(main = "Asexual", adj = 0.7, line = -12)
dev.off()


# sexual
hist(tect_hutt_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)

png(filename = file.path(plot_path, "tect_hutt_subset_sexual_enfa_hist.png"))
hist(tect_hutt_sexual_enfa_subset)
title(main = "Sexual", adj = 0.7, line = -12)
dev.off()

### 3) PCA of total e-space
tect_hutt_subset_total_pca <- total_climate_pca_plot(bg_env = tect_hutt_bg_env_subset, locs = tect_loc, genus = "Tectarchus", species = "huttoni")

tect_hutt_subset_total_pca

ggsave("tect_hutt_subset_total_pca.png",
       plot = tect_hutt_subset_total_pca,
       device = "png",
       path = plot_path,
       dpi = "retina")

# save enfa objects and remove them from the environment. They take up a lot of memory.
saveRDS(tect_hutt_sexual_enfa, file = file.path(obj_path, "tect_hutt_sexual_enfa.RDS"))
rm(tect_hutt_sexual_enfa)

saveRDS(tect_hutt_asexual_enfa, file = file.path(obj_path, "tect_hutt_asexual_enfa.RDS"))
rm(tect_hutt_asexual_enfa)

saveRDS(tect_hutt_sexual_enfa_subset,
        file = file.path(obj_path, "tect_hutt_subset_sexual_enfa.RDS"))
rm(tect_hutt_sexual_enfa_subset)

saveRDS(tect_hutt_asexual_enfa_subset,
        file = file.path(obj_path, "tect_hutt_subset_asexual_enfa.RDS"))
rm(tect_hutt_asexual_enfa_subset)
```

We're also interested in seeing if asexual populations live in more unstable climatic areas relative to sexual populations. 
```{r warning=FALSE, message=FALSE}
tect_hutt_locs_asexual <- tect_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "asexual",
         species == "huttoni",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

tect_hutt_locs_sexual <- tect_loc %>% 
  mutate(lat_long = str_c(latitude, longitude, sep = "_")) %>% 
  filter(reproductive_mode == "sexual",
         species == "huttoni",
         !duplicated(lat_long)) %>% 
  dplyr::select(longitude, latitude)

precip_asexual_tect_hutt <- raster::extract(precip_stability_scaled, tect_hutt_locs_asexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

precip_sexual_tect_hutt <- raster::extract(precip_stability_scaled, tect_hutt_locs_sexual) %>% 
  enframe(name = NULL, value = "precip_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

precip_df_tect_hutt <- bind_rows(precip_asexual_tect_hutt, precip_sexual_tect_hutt)

readr::write_csv(precip_df_tect_hutt, 
                 file.path(spread_path, "tect_hutt_precip_stability_df.csv"))

tect_hutt_precip_stability_plot <- ggplot(data = precip_df_tect_hutt, aes(x = reproductive_mode, y = precip_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

tect_hutt_precip_stability_plot

ggsave("tect_hutt_precip_stability.png",
       plot = tect_hutt_precip_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

temp_asexual_tect_hutt <- raster::extract(temp_stability_scaled, tect_hutt_locs_asexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

temp_sexual_tect_hutt <- raster::extract(temp_stability_scaled, tect_hutt_locs_sexual) %>% 
  enframe(name = NULL, value = "temp_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

temp_df_tect_hutt <- bind_rows(temp_asexual_tect_hutt, temp_sexual_tect_hutt)

readr::write_csv(temp_df_tect_hutt, 
                 file.path(spread_path, "tect_hutt_temp_stability_df.csv"))

tect_hutt_temp_stability_plot <- ggplot(data = temp_df_tect_hutt, aes(x = reproductive_mode, y = temp_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

tect_hutt_temp_stability_plot

ggsave("tect_hutt_precip_stability.png",
       plot = tect_hutt_temp_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")

overall_asexual_tect_hutt <- raster::extract(overall_stability_scaled, tect_hutt_locs_asexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "asexual")

overall_sexual_tect_hutt <- raster::extract(overall_stability_scaled, tect_hutt_locs_sexual) %>% 
  enframe(name = NULL, value = "overall_stability_scaled") %>% 
  mutate(reproductive_mode = "sexual")

overall_df_tect_hutt <- bind_rows(overall_asexual_tect_hutt, overall_sexual_tect_hutt)

readr::write_csv(overall_df_tect_hutt, 
                 file.path(spread_path, "tect_hutt_overall_stability_df.csv"))

tect_hutt_overall_stability_plot <- ggplot(data = overall_df_tect_hutt, aes(x = reproductive_mode, y = overall_stability_scaled, color = reproductive_mode)) +
  geom_boxplot(width = 0.5, color = "black", fill = "transparent") +
  geom_jitter(width = 0.2, alpha = 0.6) +
  scale_color_viridis_d(option = "magma") +
  theme_dark()

tect_hutt_overall_stability_plot

ggsave("tect_hutt_overall_stability.png",
       plot = tect_hutt_overall_stability_plot,
       device = "png",
       path = plot_path,
       dpi = "retina")
```

Put all output into species-specific subfolders.
```{r results="hide"}
tect_hutt_out_int_path <- file.path(interactive_path, "tectarchus_huttoni")
tect_hutt_out_plot_path <- file.path(plot_path, "tectarchus_huttoni")
tect_hutt_out_spread_path <- file.path(spread_path, "tectarchus_huttoni")
tect_hutt_out_obj_path <- file.path(obj_path, "tectarchus_huttoni")

# move interactive
move_to_species(in_path = interactive_path,
                out_path = tect_hutt_out_int_path,
                pattern = "tect_hutt")
# move plots
move_to_species(in_path = plot_path,
                out_path = tect_hutt_out_plot_path,
                pattern = "tect_hutt")

# move spreadsheets
move_to_species(in_path = spread_path,
                out_path = tect_hutt_out_spread_path,
                pattern = "tect_hutt")

# move objects
move_to_species(in_path = obj_path,
                out_path = tect_hutt_out_obj_path,
                pattern = "tect_hutt")
```

### Tepakiphasma
Nothing. Only one locality.

## Convenience scripts
*These scripts aren't crucial for reproducing this analysis, but were helpful for various reasons. Some of these have hard-coded paths and such, so no guarantees for use right out of the box.*


This was a script I used to take full chelsa files, crop them to New Zealand extent, and write them to a file with my personal computer. I don't have much memory, so unzipping to a temporary directory, then deleting the directory to free up space for the large files worked. 
```{r eval=FALSE}
## get chelsa data
chelsa_folder <- "/Users/connorfrench/Dropbox/Old_Mac/climate-data/chelsa_30s_bio"
zip_files <- list.files(chelsa_folder, full.names = TRUE)

# using the Unarchiver commandline tools for Mac to unzip the 7zip chelsa layers. Regular unzip() does not work with 7z zipped files
for (file in zip_files) {
  # set temp directory
  tempd <- tempdir()
  system(paste("unar", file, "-o", tempd))
  r <- raster(list.files(tempd, pattern = "*.tif", full.names = TRUE)) %>%
    crop(extent(166, 179, -48, -34))
  writeRaster(r, filename = paste0("~/Desktop/", list.files(tempd, pattern = "*.tif")), format = "GTiff")
  unlink(tempd, recursive = TRUE)
}
```

